Species associations structured by environment and land-use history promote beta-diversity in a temperate forest.

PubMed

Murphy, Stephen J; Audino, Livia D; Whitacre, James; Eck, Jenalle L; Wenzel, John W; Queenborough, Simon A; Comita, Liza S

2015-03-01

Patterns of diversity and community composition in forests are controlled by a combination of environmental factors, historical events, and stochastic or neutral mechanisms. Each of these processes has been linked to forest community assembly, but their combined contributions to alpha and beta-diversity in forests has not been well explored. Here we use variance partitioning to analyze approximately 40,000 individual trees of 49 species, collected within 137 ha of sampling area spread across a 900-ha temperate deciduous forest reserve in Pennsylvania to ask (1) To what extent is site-to-site variation in species richness and community composition of a temperate forest explained by measured environmental gradients and by spatial descriptors (used here to estimate dispersal-assembly or unmeasured, spatially structured processes)? (2) How does the incorporation of land-use history information increase the importance attributed to deterministic community assembly? and (3) How do the distributions and abundances of individual species within the community correlate with these factors? Environmental variables (i.e., topography, soils, and distance to stream), spatial descriptors (i.e., spatial eigenvectors derived from Cartesian coordinates), and land-use history variables (i.e., land-use type and intensity, forest age, and distance to road), explained about half of the variation in both species richness and community composition. Spatial descriptors explained the most variation, followed by measured environmental variables and then by land- use history. Individual species revealed variable responses to each of these sets of predictor variables. Several species were associated with stream habitats, and others were strictly delimited across opposing north- and south-facing slopes. Several species were also associated with areas that experienced recent (i.e., <100 years) human land-use impacts. These results indicate that deterministic factors, including environmental and land-use history variables, are important drivers of community response. The large amount of "unexplained" variation seen here (about 50%) is commonly observed in other such studies attempting to explain distribution and abundance patterns of plant communities. Determining whether such large fractions of unaccounted for variation are caused by a lack of sufficient data, or are an indication of stochastic features of forest communities globally, will remain an important challenge for ecologists in the future.

Environmental process descriptors for TNT, TNT-related compounds and picric acid in marine sediment slurries.

PubMed

Yost, Sally L; Pennington, Judith C; Brannon, James M; Hayes, Charolett A

2007-08-01

Process descriptors were determined for picric acid, TNT, and the TNT-related compounds 2,4DNT, 2,6DNT, 2ADNT, 4ADNT, 2,4DANT, 2,6DANT, TNB and DNB in marine sediment slurries. Three marine sediments of various physical characteristics (particle size ranging from 15 to >90% fines and total organic carbon ranging from <0.10 to 3.60%) were kept in suspension with 20ppt saline water. Concentrations of TNT and its related compounds decreased immediately upon contact with the marine sediment slurries, with aqueous concentrations slowly declining throughout the remaining test period. Sediment-water partition coefficients could not be determined for these compounds since solution phase concentrations were unstable. Kinetic rates and half-lives were influenced by the sediment properties, with the finer grained, higher organic carbon sediment being the most reactive. Aqueous concentrations of picric acid were very stable, demonstrating little partitioning to the sediments. Degradation to picramic acid was minimal, exhibiting concentrations at or just above the detection limit.

Automated transformation-invariant shape recognition through wavelet multiresolution

NASA Astrophysics Data System (ADS)

Brault, Patrice; Mounier, Hugues

2001-12-01

We present here new results in Wavelet Multi-Resolution Analysis (W-MRA) applied to shape recognition in automatic vehicle driving applications. Different types of shapes have to be recognized in this framework. They pertain to most of the objects entering the sensors field of a car. These objects can be road signs, lane separation lines, moving or static obstacles, other automotive vehicles, or visual beacons. The recognition process must be invariant to global, affine or not, transformations which are : rotation, translation and scaling. It also has to be invariant to more local, elastic, deformations like the perspective (in particular with wide angle camera lenses), and also like deformations due to environmental conditions (weather : rain, mist, light reverberation) or optical and electrical signal noises. To demonstrate our method, an initial shape, with a known contour, is compared to the same contour altered by rotation, translation, scaling and perspective. The curvature computed for each contour point is used as a main criterion in the shape matching process. The original part of this work is to use wavelet descriptors, generated with a fast orthonormal W-MRA, rather than Fourier descriptors, in order to provide a multi-resolution description of the contour to be analyzed. In such way, the intrinsic spatial localization property of wavelet descriptors can be used and the recognition process can be speeded up. The most important part of this work is to demonstrate the potential performance of Wavelet-MRA in this application of shape recognition.

Descriptors for ions and ion-pairs for use in linear free energy relationships.

PubMed

Abraham, Michael H; Acree, William E

2016-01-22

The determination of Abraham descriptors for single ions is reviewed, and equations are given for the partition of single ions from water to a number of solvents. These ions include permanent anions and cations and ionic species such as carboxylic acid anions, phenoxide anions and protonated base cations. Descriptors for a large number of ions and ionic species are listed, and equations for the prediction of Abraham descriptors for ionic species are given. The application of descriptors for ions and ionic species to physicochemical processes is given; these are to water-solvent partitions, HPLC retention data, immobilised artificial membranes, the Finkelstein reaction and diffusion in water. Applications to biological processes include brain permeation, microsomal degradation of drugs, skin permeation and human intestinal absorption. The review concludes with a section on the determination of descriptors for ion-pairs. Copyright © 2015 Elsevier B.V. All rights reserved.

Using biological effects tools to define Good Environmental Status under the European Union Marine Strategy Framework Directive.

PubMed

Lyons, B P; Thain, J E; Stentiford, G D; Hylland, K; Davies, I M; Vethaak, A D

2010-10-01

The use of biological effects tools offer enormous potential to meet the challenges outlined by the European Union Marine Strategy Framework Directive (MSFD) whereby Member States are required to develop a robust set of tools for defining 11 qualitative descriptors of Good Environmental Status (GES), such as demonstrating that "Concentrations of contaminants are at levels not giving rise to pollution effects" (GES Descriptor 8). This paper discusses the combined approach of monitoring chemical contaminant levels, along side biological effect measurements relating to the effect of pollutants, for undertaking assessments of GES across European marine regions. We outline the minimum standards that biological effects tools should meet if they are to be used for defining GES in relation to Descriptor 8 and describe the current international initiatives underway to develop assessment criteria for these biological effects techniques. Crown Copyright © 2010. Published by Elsevier Ltd. All rights reserved.

Temperature sensitivity of organic compound destruction in SCWO process.

PubMed

Tan, Yaqin; Shen, Zhemin; Guo, Weimin; Ouyang, Chuang; Jia, Jinping; Jiang, Weili; Zhou, Haiyun

2014-03-01

To study the temperature sensitivity of the destruction of organic compounds in supercritical water oxidation process (SCWO), oxidation effects of twelve chemicals in supercritical water were investigated. The SCWO reaction rates of different compounds improved to varying degrees with the increase of temperature, so the highest slope of the temperature-effect curve (imax) was defined as the maximum ratio of removal ratio to working temperature. It is an important index to stand for the temperature sensitivity effect in SCWO. It was proven that the higher imax is, the more significant the effect of temperature on the SCWO effect is. Since the high-temperature area of SCWO equipment is subject to considerable damage from fatigue, the temperature is of great significance in SCWO equipment operation. Generally, most compounds (imax > 0.25) can be completely oxidized when the reactor temperature reaches 500°C. However, some compounds (imax > 0.25) need a higher temperature for complete oxidation, up to 560°C. To analyze the correlation coefficients between imax and various molecular descriptors, a quantum chemical method was used in this study. The structures of the twelve organic compounds were optimized by the Density Functional Theory B3LYP/6-311G method, as well as their quantum properties. It was shown that six molecular descriptors were negatively correlated to imax while other three descriptors were positively correlated to imax. Among them, dipole moment had the greatest effect on the oxidation thermodynamics of the twelve organic compounds. Once a correlation between molecular descriptors and imax is established, SCWO can be run at an appropriate temperature according to molecular structure. Copyright © 2014 The Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.

A computer program for creating keyword indexes to textual data files

USGS Publications Warehouse

Moody, David W.

1972-01-01

A keyword-in-context (KWIC) or out-of-context (KWOC) index is a convenient means of organizing information. This keyword index program can be used to create either KWIC or KWOC indexes of bibliographic references or other types of information punched on. cards, typed on optical scanner sheets, or retrieved from various Department of Interior data bases using the Generalized Information Processing System (GIPSY). The index consists of a 'bibliographic' section and a keyword-section based on the permutation of. document titles, project titles, environmental impact statement titles, maps, etc. or lists of descriptors. The program can also create a back-of-the-book index to documents from a list of descriptors. By providing the user with a wide range of input and output options, the program provides the researcher, manager, or librarian with a means of-maintaining a list and index to documents in. a small library, reprint collection, or office file.

Vocabulary Development and Maintenance--Descriptors. ERIC Processing Manual, Section VIII (Part 1).

ERIC Educational Resources Information Center

Houston, Jim, Ed.

Comprehensive rules, guidelines, and examples are provided for use by ERIC indexers and lexicographers in developing and maintaining the "Thesaurus of ERIC Descriptors." Evaluation and decision criteria, research procedures, and inputting details for adding new Descriptors are documented. Instructions for modifying existing Thesaurus…

Contemporary group estimates adjusted for climatic effects provide a finer definition of the unknown environmental challenges experienced by growing pigs.

PubMed

Guy, S Z Y; Li, L; Thomson, P C; Hermesch, S

2017-12-01

Environmental descriptors derived from mean performances of contemporary groups (CGs) are assumed to capture any known and unknown environmental challenges. The objective of this paper was to obtain a finer definition of the unknown challenges, by adjusting CG estimates for the known climatic effects of monthly maximum air temperature (MaxT), minimum air temperature (MinT) and monthly rainfall (Rain). As the unknown component could include infection challenges, these refined descriptors may help to better model varying responses of sire progeny to environmental infection challenges for the definition of disease resilience. Data were recorded from 1999 to 2013 at a piggery in south-east Queensland, Australia (n = 31,230). Firstly, CG estimates of average daily gain (ADG) and backfat (BF) were adjusted for MaxT, MinT and Rain, which were fitted as splines. In the models used to derive CG estimates for ADG, MaxT and MinT were significant variables. The models that contained these significant climatic variables had CG estimates with a lower variance compared to models without significant climatic variables. Variance component estimates were similar across all models, suggesting that these significant climatic variables accounted for some known environmental variation captured in CG estimates. No climatic variables were significant in the models used to derive the CG estimates for BF. These CG estimates were used to categorize environments. There was no observable sire by environment interaction (Sire×E) for ADG when using the environmental descriptors based on CG estimates on BF. For the environmental descriptors based on CG estimates of ADG, there was significant Sire×E only when MinT was included in the model (p = .01). Therefore, this new definition of the environment, preadjusted by MinT, increased the ability to detect Sire×E. While the unknown challenges captured in refined CG estimates need verification for infection challenges, this may provide a practical approach for the genetic improvement of disease resilience. © 2017 Blackwell Verlag GmbH.

Idiopathic environmental intolerance: Part 1: A causation analysis applying Bradford Hill's criteria to the toxicogenic theory.

PubMed

Staudenmayer, Herman; Binkley, Karen E; Leznoff, Arthur; Phillips, Scott

2003-01-01

Idiopathic environmental intolerance (IEI) is a descriptor for a phenomenon that has many names including environmental illness, multiple chemical sensitivity and chemical intolerance. Toxicogenic and psychogenic theories have been proposed to explain IEI. This paper presents a causality analysis of the toxicogenic theory using Bradford Hill's nine criteria (strength, consistency, specificity, temporality, biological gradient, biological plausibility, coherence, experimental intervention and analogy) and an additional criteria (reversibility) and reviews critically the scientific literature on the topic. The results of this analysis indicate that the toxicogenic theory fails all of these criteria. There is no convincing evidence to support the fundamental postulate that IEI has a toxic aetiology; the hypothesised biological processes and mechanisms are implausible.

Completion processing for data communications instructions

DOEpatents

Blocksome, Michael A.; Kumar, Sameer; Jeffrey, Parker J.

2014-06-10

Completion processing of data communications instructions in a distributed computing environment with computers coupled for data communications through communications adapters and an active messaging interface (`AMI`), injecting for data communications instructions into slots in an injection FIFO buffer a transfer descriptor, at least some of the instructions specifying callback functions; injecting a completion descriptor for each instruction that specifies a callback function into an injection FIFO buffer slot having a corresponding slot in a pending callback list; listing in the pending callback list callback functions specified by data communications instructions; processing each descriptor in the injection FIFO buffer, setting a bit in a completion bit mask corresponding to the slot in the FIFO where the completion descriptor was injected; and calling by the AMI any callback functions in the pending callback list as indicated by set bits in the completion bit mask.

Environmental Transport and Fate Process Descriptors for Propellant Compounds

DTIC Science & Technology

2006-06-01

compositional changes that occur when propellant pellets and flakes are immersed in stirred aqueous solutions for 0 to 220 hours. ERDC/EL TR-06-7 2... solution , NQ concen- tration remains constant in heated, dilute hydrochloric acid, but will hydrolyze to NH3, N2O, and CO2 at pH greater than 10...with values between 36 and 300 mg/L (Table 2). Hydrolysis of DPA was inferred from decreased Daphnia toxicity when aged (30-day) aqueous solutions

Direct memory access transfer completion notification

DOEpatents

Archer, Charles J. , Blocksome; Michael A. , Parker; Jeffrey, J [Rochester, MN

2011-02-15

Methods, systems, and products are disclosed for DMA transfer completion notification that include: inserting, by an origin DMA on an origin node in an origin injection FIFO, a data descriptor for an application message; inserting, by the origin DMA, a reflection descriptor in the origin injection FIFO, the reflection descriptor specifying a remote get operation for injecting a completion notification descriptor in a reflection injection FIFO on a reflection node; transferring, by the origin DMA to a target node, the message in dependence upon the data descriptor; in response to completing the message transfer, transferring, by the origin DMA to the reflection node, the completion notification descriptor in dependence upon the reflection descriptor; receiving, by the origin DMA from the reflection node, a completion packet; and notifying, by the origin DMA in response to receiving the completion packet, the origin node's processing core that the message transfer is complete.

Abnormal brain processing of affective and sensory pain descriptors in chronic pain patients.

PubMed

Sitges, Carolina; García-Herrera, Manuel; Pericás, Miquel; Collado, Dolores; Truyols, Magdalena; Montoya, Pedro

2007-12-01

Previous research has suggested that chronic pain patients might be particularly vulnerable to the effects of negative mood during information processing. However, there is little evidence for abnormal brain processing of affective and sensory pain-related information in chronic pain. Behavioral and brain responses, to pain descriptors and pleasant words, were examined in chronic pain patients and healthy controls during a self-endorsement task. Eighteen patients with fibromyalgia (FM), 18 patients with chronic musculoskeletal pain due to identifiable physical injury (MSK), and 16 healthy controls were asked to decide whether word targets described their current or past experience of pain. The number of self-endorsed words, elapsed time to endorse the words, and event-related potentials (ERPs) elicited by words, were recorded. Data revealed that chronic pain patients used more affective and sensory pain descriptors, and were slower in responding to self-endorsed pain descriptors than to pleasant words. In addition, it was found that affective pain descriptors elicited significantly more enhanced positive ERP amplitudes than pleasant words in MSK pain patients; whereas sensory pain descriptors elicited greater positive ERP amplitudes than affective pain words in healthy controls. These data support the notion of abnormal information processing in chronic pain patients, which might be characterized by a lack of dissociation between sensory and affective components of pain-related information, and by an exaggerated rumination over word meaning during the encoding of self-referent information about pain.

Completion processing for data communications instructions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blocksome, Michael A.; Kumar, Sameer; Parker, Jeffrey J.

Completion processing of data communications instructions in a distributed computing environment with computers coupled for data communications through communications adapters and an active messaging interface (`AMI`), injecting for data communications instructions into slots in an injection FIFO buffer a transfer descriptor, at least some of the instructions specifying callback functions; injecting a completion descriptor for each instruction that specifies a callback function into an injection FIFO buffer slot having a corresponding slot in a pending callback list; listing in the pending callback list callback functions specified by data communications instructions; processing each descriptor in the injection FIFO buffer, setting amore » bit in a completion bit mask corresponding to the slot in the FIFO where the completion descriptor was injected; and calling by the AMI any callback functions in the pending callback list as indicated by set bits in the completion bit mask.« less

Dual descriptors within the framework of spin-polarized density functional theory.

PubMed

Chamorro, E; Pérez, P; Duque, M; De Proft, F; Geerlings, P

2008-08-14

Spin-polarized density functional theory (SP-DFT) allows both the analysis of charge-transfer (e.g., electrophilic and nucleophilic reactivity) and of spin-polarization processes (e.g., photophysical changes arising from electron transitions). In analogy with the dual descriptor introduced by Morell et al. [J. Phys. Chem. A 109, 205 (2005)], we introduce new dual descriptors intended to simultaneously give information of the molecular regions where the spin-polarization process linking states of different multiplicity will drive electron density and spin density changes. The electronic charge and spin rearrangement in the spin forbidden radiative transitions S(0)-->T(n,pi(*)) and S(0)-->T(pi,pi(*)) in formaldehyde and ethylene, respectively, have been used as benchmark examples illustrating the usefulness of the new spin-polarization dual descriptors. These quantities indicate those regions where spin-orbit coupling effects are at work in such processes. Additionally, the qualitative relationship between the topology of the spin-polarization dual descriptors and the vertical singlet triplet energy gap in simple substituted carbene series has been also discussed. It is shown that the electron density and spin density rearrangements arise in agreement with spectroscopic experimental evidence and other theoretical results on the selected target systems.

[The use of Cantonese pain descriptors among healthy young adults in Hong Kong].

PubMed

Chung, W Y; Wong, C H; Yang, J C; Tan, P P

1998-12-01

The interpretation and expression of pain are closely related to an individual's social and cultural background. To convey messages on pain, language and words (pain descriptors) is particularly significant in assessment and evaluation of pain severity and its management. Therefore, the study of pain descriptors is crucial in clinical practice. It was of exploratory-descriptive design. Samples were recruited by convenience. Data were collected by structured self-administered questionnaire. Data obtained included demographic information and pain descriptors used by the subjects in various pain conditions. Data were analyzed by descriptive statistics. Pain descriptors were categorized according to nature, process, intensity, aggravating factors, accompanying symptoms and behavioral manifestation. Total number of pain descriptors (in Cantonese) based on real pain experience was 3017, mean was 3 (n = 986). The commonest used descriptors was the nature of pain (41%). The intensity of pain constituted 20%. There was no significant difference in the number of pain descriptors between male and female. However, there was a significant difference between the type of pain descriptors used (Mfemale = 526, Mmale = 453, Z = -2.9729, p = 0.0029). There were also significant differences in the use of pain descriptors among the various age groups (X2 = 15.0157, df = 4, P = 0.0047) and educational levels (X2 = 11.2443, df = 4, P = 0.0240). The types of descriptors used increased with an increase in age and education levels. This exploratory-descriptive study explores the use of pain descriptors among Chinese young adults in Hong Kong. The result shows that female use more pain descriptors than male. The pain descriptors that female used are mostly of nature type. The similarities and differences in findings with those of the Ho's (1991) are compared.

Receptive fields selection for binary feature description.

PubMed

Fan, Bin; Kong, Qingqun; Trzcinski, Tomasz; Wang, Zhiheng; Pan, Chunhong; Fua, Pascal

2014-06-01

Feature description for local image patch is widely used in computer vision. While the conventional way to design local descriptor is based on expert experience and knowledge, learning-based methods for designing local descriptor become more and more popular because of their good performance and data-driven property. This paper proposes a novel data-driven method for designing binary feature descriptor, which we call receptive fields descriptor (RFD). Technically, RFD is constructed by thresholding responses of a set of receptive fields, which are selected from a large number of candidates according to their distinctiveness and correlations in a greedy way. Using two different kinds of receptive fields (namely rectangular pooling area and Gaussian pooling area) for selection, we obtain two binary descriptors RFDR and RFDG .accordingly. Image matching experiments on the well-known patch data set and Oxford data set demonstrate that RFD significantly outperforms the state-of-the-art binary descriptors, and is comparable with the best float-valued descriptors at a fraction of processing time. Finally, experiments on object recognition tasks confirm that both RFDR and RFDG successfully bridge the performance gap between binary descriptors and their floating-point competitors.

Alignment-independent comparison of binding sites based on DrugScore potential fields encoded by 3D Zernike descriptors.

PubMed

Nisius, Britta; Gohlke, Holger

2012-09-24

Analyzing protein binding sites provides detailed insights into the biological processes proteins are involved in, e.g., into drug-target interactions, and so is of crucial importance in drug discovery. Herein, we present novel alignment-independent binding site descriptors based on DrugScore potential fields. The potential fields are transformed to a set of information-rich descriptors using a series expansion in 3D Zernike polynomials. The resulting Zernike descriptors show a promising performance in detecting similarities among proteins with low pairwise sequence identities that bind identical ligands, as well as within subfamilies of one target class. Furthermore, the Zernike descriptors are robust against structural variations among protein binding sites. Finally, the Zernike descriptors show a high data compression power, and computing similarities between binding sites based on these descriptors is highly efficient. Consequently, the Zernike descriptors are a useful tool for computational binding site analysis, e.g., to predict the function of novel proteins, off-targets for drug candidates, or novel targets for known drugs.

PROFEAT Update: A Protein Features Web Server with Added Facility to Compute Network Descriptors for Studying Omics-Derived Networks.

PubMed

Zhang, P; Tao, L; Zeng, X; Qin, C; Chen, S Y; Zhu, F; Yang, S Y; Li, Z R; Chen, W P; Chen, Y Z

2017-02-03

The studies of biological, disease, and pharmacological networks are facilitated by the systems-level investigations using computational tools. In particular, the network descriptors developed in other disciplines have found increasing applications in the study of the protein, gene regulatory, metabolic, disease, and drug-targeted networks. Facilities are provided by the public web servers for computing network descriptors, but many descriptors are not covered, including those used or useful for biological studies. We upgraded the PROFEAT web server http://bidd2.nus.edu.sg/cgi-bin/profeat2016/main.cgi for computing up to 329 network descriptors and protein-protein interaction descriptors. PROFEAT network descriptors comprehensively describe the topological and connectivity characteristics of unweighted (uniform binding constants and molecular levels), edge-weighted (varying binding constants), node-weighted (varying molecular levels), edge-node-weighted (varying binding constants and molecular levels), and directed (oriented processes) networks. The usefulness of the network descriptors is illustrated by the literature-reported studies of the biological networks derived from the genome, interactome, transcriptome, metabolome, and diseasome profiles. Copyright © 2016 Elsevier Ltd. All rights reserved.

Future generations, environmental ethics, and global environmental change

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tonn, B.E.

1994-12-31

The elements of a methodology to be employed by the global community to investigate the consequences of global environmental change upon future generations and global ecosystems are outlined in this paper. The methodology is comprised of two major components: A possible future worlds model; and a formal, citizen-oriented process to judge whether the possible future worlds potentially inheritable by future generations meet obligational standards. A broad array of descriptors of future worlds can be encompassed within this framework, including survival of ecosystems and other species and satisfaction of human concerns. The methodology expresses fundamental psychological motivations and human myths journey,more » renewal, mother earth, and being-in-nature-and incorporates several viewpoints on obligations to future generations-maintaining options, fairness, humility, and the cause of humanity. The methodology overcomes several severe drawbacks of the economic-based methods most commonly used for global environmental policy analysis.« less

Relations between water physico-chemistry and benthic algal communities in a northern Canadian watershed: defining reference conditions using multiple descriptors of community structure.

PubMed

Thomas, Kathryn E; Hall, Roland I; Scrimgeour, Garry J

2015-09-01

Defining reference conditions is central to identifying environmental effects of anthropogenic activities. Using a watershed approach, we quantified reference conditions for benthic algal communities and their relations to physico-chemical conditions in rivers in the South Nahanni River watershed, NWT, Canada, in 2008 and 2009. We also compared the ability of three descriptors that vary in terms of analytical costs to define algal community structure based on relative abundances of (i) all algal taxa, (ii) only diatom taxa, and (iii) photosynthetic pigments. Ordination analyses showed that variance in algal community structure was strongly related to gradients in environmental variables describing water physico-chemistry, stream habitats, and sub-watershed structure. Water physico-chemistry and local watershed-scale descriptors differed significantly between algal communities from sites in the Selwyn Mountain ecoregion compared to sites in the Nahanni-Hyland ecoregions. Distinct differences in algal community types between ecoregions were apparent irrespective of whether algal community structure was defined using all algal taxa, diatom taxa, or photosynthetic pigments. Two algal community types were highly predictable using environmental variables, a core consideration in the development of Reference Condition Approach (RCA) models. These results suggest that assessments of environmental impacts could be completed using RCA models for each ecoregion. We suggest that use of algal pigments, a high through-put analysis, is a promising alternative compared to more labor-intensive and costly taxonomic approaches for defining algal community structure.

Descriptors of sensation confirm the multidimensional nature of desire to void.

PubMed

Das, Rebekah; Buckley, Jonathan D; Williams, Marie T

2015-02-01

To collect and categorize descriptors of "desire to void" sensation, determine the reliability of descriptor categories and assess whether descriptor categories discriminate between people with and without symptoms of overactive bladder. This observational, repeated measures study involved 64 Australian volunteers (47 female), aged 50 years or more, with and without symptoms of overactive bladder. Descriptors of desire to void sensation were derived from a structured interview (conducted on two occasions, 1 week apart). Descriptors were recorded verbatim and categorized in a three-stage process. Overactive bladder status was determined by the Overactive Bladder Awareness Tool and the Overactive Bladder Symptom Score. McNemar's test assessed the reliability of descriptors volunteered between two occasions and Partial Least Squares Regression determined whether language categories discriminated according to overactive bladder status. Post hoc Chi squared analysis and relative risk calculation determined the size and direction of overactive bladder prediction. Thirteen language categories (Urgency, Fullness, Pressure, Tickle/tingle, Pain/ache, Heavy, Normal, Intense, Sudden, Annoying, Uncomfortable, Anxiety, and Unique somatic) encapsulated 344 descriptors of sensation. Descriptor categories were stable between two interviews. The categories "Urgency" and "Fullness" predicted overactive bladder status. Participants who volunteered "Urgency" descriptors were twice as likely to have overactive bladder and participants who volunteered "Fullness" descriptors were almost three times as likely not to have overactive bladder. The sensation of desire to void is reliably described over sessions separated by a week, the language used reflects multiple dimensions of sensation, and can predict overactive bladder status. © 2013 Wiley Periodicals, Inc.

Revisiting caffeate's capabilities as a complexation agent to silver cation in mining processes by means of the dual descriptor--a conceptual DFT approach.

PubMed

Martínez-Araya, Jorge Ignacio

2012-09-01

Caffeic acid (C(9)H(8)O(4)) and its conjugate base C(9)H(7)O(4) (-) (anionic form-known as caffeate) were analyzed computationally through the use of quantum chemistry to assess their intrinsic global and local reactivity using the tools of conceptual density functional theory. The anionic form was found to be better at coordinating the silver cation than caffeic acid thus suggesting the use of caffeate as a complexation agent. The complexation capability of caffeate was compared with that of some of the most common ligand agents used to coordinate silver cations. Local reactivity descriptors allowed identification of the preferred sites on caffeate for silver cation coordination thus generating a plausible silver complex. All silver complexes were analyzed thermodynamically considering interaction energies in both gas and aqueous phases; the complexation free energy in aqueous phase was also determined. These results suggest that more attention be paid to the caffeate anion and its derivatives because this work has shed new light on the behavior of this anion in the recovery of silver cations that could be exploited in silver mining processes in a environmentally friendly way.

Modular Chemical Descriptor Language (MCDL): Stereochemical modules

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gakh, Andrei A; Burnett, Michael N; Trepalin, Sergei V.

2011-01-01

In our previous papers we introduced the Modular Chemical Descriptor Language (MCDL) for providing a linear representation of chemical information. A subsequent development was the MCDL Java Chemical Structure Editor which is capable of drawing chemical structures from linear representations and generating MCDL descriptors from structures. In this paper we present MCDL modules and accompanying software that incorporate unique representation of molecular stereochemistry based on Cahn-Ingold-Prelog and Fischer ideas in constructing stereoisomer descriptors. The paper also contains additional discussions regarding canonical representation of stereochemical isomers, and brief algorithm descriptions of the open source LINDES, Java applet, and Open Babel MCDLmore » processing module software packages. Testing of the upgraded MCDL Java Chemical Structure Editor on compounds taken from several large and diverse chemical databases demonstrated satisfactory performance for storage and processing of stereochemical information in MCDL format.« less

Visual feature discrimination versus compression ratio for polygonal shape descriptors

NASA Astrophysics Data System (ADS)

Heuer, Joerg; Sanahuja, Francesc; Kaup, Andre

2000-10-01

In the last decade several methods for low level indexing of visual features appeared. Most often these were evaluated with respect to their discrimination power using measures like precision and recall. Accordingly, the targeted application was indexing of visual data within databases. During the standardization process of MPEG-7 the view on indexing of visual data changed, taking also communication aspects into account where coding efficiency is important. Even if the descriptors used for indexing are small compared to the size of images, it is recognized that there can be several descriptors linked to an image, characterizing different features and regions. Beside the importance of a small memory footprint for the transmission of the descriptor and the memory footprint in a database, eventually the search and filtering can be sped up by reducing the dimensionality of the descriptor if the metric of the matching can be adjusted. Based on a polygon shape descriptor presented for MPEG-7 this paper compares the discrimination power versus memory consumption of the descriptor. Different methods based on quantization are presented and their effect on the retrieval performance are measured. Finally an optimized computation of the descriptor is presented.

Hybrid Histogram Descriptor: A Fusion Feature Representation for Image Retrieval.

PubMed

Feng, Qinghe; Hao, Qiaohong; Chen, Yuqi; Yi, Yugen; Wei, Ying; Dai, Jiangyan

2018-06-15

Currently, visual sensors are becoming increasingly affordable and fashionable, acceleratingly the increasing number of image data. Image retrieval has attracted increasing interest due to space exploration, industrial, and biomedical applications. Nevertheless, designing effective feature representation is acknowledged as a hard yet fundamental issue. This paper presents a fusion feature representation called a hybrid histogram descriptor (HHD) for image retrieval. The proposed descriptor comprises two histograms jointly: a perceptually uniform histogram which is extracted by exploiting the color and edge orientation information in perceptually uniform regions; and a motif co-occurrence histogram which is acquired by calculating the probability of a pair of motif patterns. To evaluate the performance, we benchmarked the proposed descriptor on RSSCN7, AID, Outex-00013, Outex-00014 and ETHZ-53 datasets. Experimental results suggest that the proposed descriptor is more effective and robust than ten recent fusion-based descriptors under the content-based image retrieval framework. The computational complexity was also analyzed to give an in-depth evaluation. Furthermore, compared with the state-of-the-art convolutional neural network (CNN)-based descriptors, the proposed descriptor also achieves comparable performance, but does not require any training process.

Structure-Activity Relationships for Rates of Aromatic Amine Oxidation by Manganese Dioxide.

PubMed

Salter-Blanc, Alexandra J; Bylaska, Eric J; Lyon, Molly A; Ness, Stuart C; Tratnyek, Paul G

2016-05-17

New energetic compounds are designed to minimize their potential environmental impacts, which includes their transformation and the fate and effects of their transformation products. The nitro groups of energetic compounds are readily reduced to amines, and the resulting aromatic amines are subject to oxidation and coupling reactions. Manganese dioxide (MnO2) is a common environmental oxidant and model system for kinetic studies of aromatic amine oxidation. In this study, a training set of new and previously reported kinetic data for the oxidation of model and energetic-derived aromatic amines was assembled and subjected to correlation analysis against descriptor variables that ranged from general purpose [Hammett σ constants (σ(-)), pKas of the amines, and energies of the highest occupied molecular orbital (EHOMO)] to specific for the likely rate-limiting step [one-electron oxidation potentials (Eox)]. The selection of calculated descriptors (pKa, EHOMO, and Eox) was based on validation with experimental data. All of the correlations gave satisfactory quantitative structure-activity relationships (QSARs), but they improved with the specificity of the descriptor. The scope of correlation analysis was extended beyond MnO2 to include literature data on aromatic amine oxidation by other environmentally relevant oxidants (ozone, chlorine dioxide, and phosphate and carbonate radicals) by correlating relative rate constants (normalized to 4-chloroaniline) to EHOMO (calculated with a modest level of theory).

Climate and Human Pressure Constraints Co-Explain Regional Plant Invasion at Different Spatial Scales

PubMed Central

García-Baquero, Gonzalo; Caño, Lidia; Biurrun, Idoia; García-Mijangos, Itziar; Loidi, Javier; Herrera, Mercedes

2016-01-01

Alien species invasion represents a global threat to biodiversity and ecosystems. Explaining invasion patterns in terms of environmental constraints will help us to assess invasion risks and plan control strategies. We aim to identify plant invasion patterns in the Basque Country (Spain), and to determine the effects of climate and human pressure on that pattern. We modeled the regional distribution of 89 invasive plant species using two approaches. First, distance-based Moran’s eigenvector maps were used to partition variation in the invasive species richness, S, into spatial components at broad and fine scales; redundancy analysis was then used to explain those components on the basis of climate and human pressure descriptors. Second, we used generalized additive mixed modeling to fit species-specific responses to the same descriptors. Climate and human pressure descriptors have different effects on S at different spatial scales. Broad-scale spatially structured temperature and precipitation, and fine-scale spatially structured human population density and percentage of natural and semi-natural areas, explained altogether 38.7% of the total variance. The distribution of 84% of the individually tested species was related to either temperature, precipitation or both, and 68% was related to either population density or natural and semi-natural areas, displaying similar responses. The spatial pattern of the invasive species richness is strongly environmentally forced, mainly by climate factors. Since individual species responses were proved to be both similarly constrained in shape and explained variance by the same environmental factors, we conclude that the pattern of invasive species richness results from individual species’ environmental preferences. PMID:27741276

Evaluation of MPEG-7-Based Audio Descriptors for Animal Voice Recognition over Wireless Acoustic Sensor Networks.

PubMed

Luque, Joaquín; Larios, Diego F; Personal, Enrique; Barbancho, Julio; León, Carlos

2016-05-18

Environmental audio monitoring is a huge area of interest for biologists all over the world. This is why some audio monitoring system have been proposed in the literature, which can be classified into two different approaches: acquirement and compression of all audio patterns in order to send them as raw data to a main server; or specific recognition systems based on audio patterns. The first approach presents the drawback of a high amount of information to be stored in a main server. Moreover, this information requires a considerable amount of effort to be analyzed. The second approach has the drawback of its lack of scalability when new patterns need to be detected. To overcome these limitations, this paper proposes an environmental Wireless Acoustic Sensor Network architecture focused on use of generic descriptors based on an MPEG-7 standard. These descriptors demonstrate it to be suitable to be used in the recognition of different patterns, allowing a high scalability. The proposed parameters have been tested to recognize different behaviors of two anuran species that live in Spanish natural parks; the Epidalea calamita and the Alytes obstetricans toads, demonstrating to have a high classification performance.

High throughput heuristics for prioritizing human exposure to environmental chemicals.

PubMed

Wambaugh, John F; Wang, Anran; Dionisio, Kathie L; Frame, Alicia; Egeghy, Peter; Judson, Richard; Setzer, R Woodrow

2014-11-04

The risk posed to human health by any of the thousands of untested anthropogenic chemicals in our environment is a function of both the hazard presented by the chemical and the extent of exposure. However, many chemicals lack estimates of exposure intake, limiting the understanding of health risks. We aim to develop a rapid heuristic method to determine potential human exposure to chemicals for application to the thousands of chemicals with little or no exposure data. We used Bayesian methodology to infer ranges of exposure consistent with biomarkers identified in urine samples from the U.S. population by the National Health and Nutrition Examination Survey (NHANES). We performed linear regression on inferred exposure for demographic subsets of NHANES demarked by age, gender, and weight using chemical descriptors and use information from multiple databases and structure-based calculators. Five descriptors are capable of explaining roughly 50% of the variability in geometric means across 106 NHANES chemicals for all the demographic groups, including children aged 6-11. We use these descriptors to estimate human exposure to 7968 chemicals, the majority of which have no other quantitative exposure prediction. For thousands of chemicals with no other information, this approach allows forecasting of average exposure intake of environmental chemicals.

Evaluation of MPEG-7-Based Audio Descriptors for Animal Voice Recognition over Wireless Acoustic Sensor Networks

PubMed Central

Luque, Joaquín; Larios, Diego F.; Personal, Enrique; Barbancho, Julio; León, Carlos

2016-01-01

Environmental audio monitoring is a huge area of interest for biologists all over the world. This is why some audio monitoring system have been proposed in the literature, which can be classified into two different approaches: acquirement and compression of all audio patterns in order to send them as raw data to a main server; or specific recognition systems based on audio patterns. The first approach presents the drawback of a high amount of information to be stored in a main server. Moreover, this information requires a considerable amount of effort to be analyzed. The second approach has the drawback of its lack of scalability when new patterns need to be detected. To overcome these limitations, this paper proposes an environmental Wireless Acoustic Sensor Network architecture focused on use of generic descriptors based on an MPEG-7 standard. These descriptors demonstrate it to be suitable to be used in the recognition of different patterns, allowing a high scalability. The proposed parameters have been tested to recognize different behaviors of two anuran species that live in Spanish natural parks; the Epidalea calamita and the Alytes obstetricans toads, demonstrating to have a high classification performance. PMID:27213375

SVM prediction of ligand-binding sites in bacterial lipoproteins employing shape and physio-chemical descriptors.

PubMed

Kadam, Kiran; Prabhakar, Prashant; Jayaraman, V K

2012-11-01

Bacterial lipoproteins play critical roles in various physiological processes including the maintenance of pathogenicity and numbers of them are being considered as potential candidates for generating novel vaccines. In this work, we put forth an algorithm to identify and predict ligand-binding sites in bacterial lipoproteins. The method uses three types of pocket descriptors, namely fpocket descriptors, 3D Zernike descriptors and shell descriptors, and combines them with Support Vector Machine (SVM) method for the classification. The three types of descriptors represent shape-based properties of the pocket as well as its local physio-chemical features. All three types of descriptors, along with their hybrid combinations are evaluated with SVM and to improve classification performance, WEKA-InfoGain feature selection is applied. Results obtained in the study show that the classifier successfully differentiates between ligand-binding and non-binding pockets. For the combination of three types of descriptors, 10 fold cross-validation accuracy of 86.83% is obtained for training while the selected model achieved test Matthews Correlation Coefficient (MCC) of 0.534. Individually or in combination with new and existing methods, our model can be a very useful tool for the prediction of potential ligand-binding sites in bacterial lipoproteins.

Learning to assign binary weights to binary descriptor

NASA Astrophysics Data System (ADS)

Huang, Zhoudi; Wei, Zhenzhong; Zhang, Guangjun

2016-10-01

Constructing robust binary local feature descriptors are receiving increasing interest due to their binary nature, which can enable fast processing while requiring significantly less memory than their floating-point competitors. To bridge the performance gap between the binary and floating-point descriptors without increasing the computational cost of computing and matching, optimal binary weights are learning to assign to binary descriptor for considering each bit might contribute differently to the distinctiveness and robustness. Technically, a large-scale regularized optimization method is applied to learn float weights for each bit of the binary descriptor. Furthermore, binary approximation for the float weights is performed by utilizing an efficient alternatively greedy strategy, which can significantly improve the discriminative power while preserve fast matching advantage. Extensive experimental results on two challenging datasets (Brown dataset and Oxford dataset) demonstrate the effectiveness and efficiency of the proposed method.

Solvation descriptors for the polychloronaphthalenes: estimation of some physicochemical properties.

PubMed

Abraham, M H; al-Hussaini, A J

2001-08-01

Solvation descriptors for the 75 polychloronaphthalenes have been derived from literature data on various properties. These descriptors (S, the dipolarity/polarizability; B, the hydrogen bond basicity; L, the logarithm of the gas-hexadecane partition coefficient; E, the excess molar refraction; V, the McGowan volume) have been used to estimate properties that may be environmentally relevant. Thus, for all 75 polychloronaphthalenes, we estimate values for the water-octanol partition coefficient, as log POCT, the aqueous solubility, as log S, the gas-water partition coefficient, as log KW, and the gas-dry octanol partition coefficient, as log KOCT. We further show that it is trivial to estimate other properties for all 75 polychloronaphthalenes; these properties include a number of gas-solvent and water-solvent partitions, air-plant and water-plant partitions, and permeation of human skin from water.

OPERA models for predicting physicochemical properties and environmental fate endpoints.

PubMed

Mansouri, Kamel; Grulke, Chris M; Judson, Richard S; Williams, Antony J

2018-03-08

The collection of chemical structure information and associated experimental data for quantitative structure-activity/property relationship (QSAR/QSPR) modeling is facilitated by an increasing number of public databases containing large amounts of useful data. However, the performance of QSAR models highly depends on the quality of the data and modeling methodology used. This study aims to develop robust QSAR/QSPR models for chemical properties of environmental interest that can be used for regulatory purposes. This study primarily uses data from the publicly available PHYSPROP database consisting of a set of 13 common physicochemical and environmental fate properties. These datasets have undergone extensive curation using an automated workflow to select only high-quality data, and the chemical structures were standardized prior to calculation of the molecular descriptors. The modeling procedure was developed based on the five Organization for Economic Cooperation and Development (OECD) principles for QSAR models. A weighted k-nearest neighbor approach was adopted using a minimum number of required descriptors calculated using PaDEL, an open-source software. The genetic algorithms selected only the most pertinent and mechanistically interpretable descriptors (2-15, with an average of 11 descriptors). The sizes of the modeled datasets varied from 150 chemicals for biodegradability half-life to 14,050 chemicals for logP, with an average of 3222 chemicals across all endpoints. The optimal models were built on randomly selected training sets (75%) and validated using fivefold cross-validation (CV) and test sets (25%). The CV Q 2 of the models varied from 0.72 to 0.95, with an average of 0.86 and an R 2 test value from 0.71 to 0.96, with an average of 0.82. Modeling and performance details are described in QSAR model reporting format and were validated by the European Commission's Joint Research Center to be OECD compliant. All models are freely available as an open-source, command-line application called OPEn structure-activity/property Relationship App (OPERA). OPERA models were applied to more than 750,000 chemicals to produce freely available predicted data on the U.S. Environmental Protection Agency's CompTox Chemistry Dashboard.

Convolution Comparison Pattern: An Efficient Local Image Descriptor for Fingerprint Liveness Detection

PubMed Central

Gottschlich, Carsten

2016-01-01

We present a new type of local image descriptor which yields binary patterns from small image patches. For the application to fingerprint liveness detection, we achieve rotation invariant image patches by taking the fingerprint segmentation and orientation field into account. We compute the discrete cosine transform (DCT) for these rotation invariant patches and attain binary patterns by comparing pairs of two DCT coefficients. These patterns are summarized into one or more histograms per image. Each histogram comprises the relative frequencies of pattern occurrences. Multiple histograms are concatenated and the resulting feature vector is used for image classification. We name this novel type of descriptor convolution comparison pattern (CCP). Experimental results show the usefulness of the proposed CCP descriptor for fingerprint liveness detection. CCP outperforms other local image descriptors such as LBP, LPQ and WLD on the LivDet 2013 benchmark. The CCP descriptor is a general type of local image descriptor which we expect to prove useful in areas beyond fingerprint liveness detection such as biological and medical image processing, texture recognition, face recognition and iris recognition, liveness detection for face and iris images, and machine vision for surface inspection and material classification. PMID:26844544

Use of Cell Viability Assay Data Improves the Prediction Accuracy of Conventional Quantitative Structure–Activity Relationship Models of Animal Carcinogenicity

PubMed Central

Zhu, Hao; Rusyn, Ivan; Richard, Ann; Tropsha, Alexander

2008-01-01

Background To develop efficient approaches for rapid evaluation of chemical toxicity and human health risk of environmental compounds, the National Toxicology Program (NTP) in collaboration with the National Center for Chemical Genomics has initiated a project on high-throughput screening (HTS) of environmental chemicals. The first HTS results for a set of 1,408 compounds tested for their effects on cell viability in six different cell lines have recently become available via PubChem. Objectives We have explored these data in terms of their utility for predicting adverse health effects of the environmental agents. Methods and results Initially, the classification k nearest neighbor (kNN) quantitative structure–activity relationship (QSAR) modeling method was applied to the HTS data only, for a curated data set of 384 compounds. The resulting models had prediction accuracies for training, test (containing 275 compounds together), and external validation (109 compounds) sets as high as 89%, 71%, and 74%, respectively. We then asked if HTS results could be of value in predicting rodent carcinogenicity. We identified 383 compounds for which data were available from both the Berkeley Carcinogenic Potency Database and NTP–HTS studies. We found that compounds classified by HTS as “actives” in at least one cell line were likely to be rodent carcinogens (sensitivity 77%); however, HTS “inactives” were far less informative (specificity 46%). Using chemical descriptors only, kNN QSAR modeling resulted in 62.3% prediction accuracy for rodent carcinogenicity applied to this data set. Importantly, the prediction accuracy of the model was significantly improved (72.7%) when chemical descriptors were augmented by HTS data, which were regarded as biological descriptors. Conclusions Our studies suggest that combining NTP–HTS profiles with conventional chemical descriptors could considerably improve the predictive power of computational approaches in toxicology. PMID:18414635

Reproducibility of the NEPTUNE descriptor-based scoring system on whole-slide images and histologic and ultrastructural digital images.

PubMed

Barisoni, Laura; Troost, Jonathan P; Nast, Cynthia; Bagnasco, Serena; Avila-Casado, Carmen; Hodgin, Jeffrey; Palmer, Matthew; Rosenberg, Avi; Gasim, Adil; Liensziewski, Chrysta; Merlino, Lino; Chien, Hui-Ping; Chang, Anthony; Meehan, Shane M; Gaut, Joseph; Song, Peter; Holzman, Lawrence; Gibson, Debbie; Kretzler, Matthias; Gillespie, Brenda W; Hewitt, Stephen M

2016-07-01

The multicenter Nephrotic Syndrome Study Network (NEPTUNE) digital pathology scoring system employs a novel and comprehensive methodology to document pathologic features from whole-slide images, immunofluorescence and ultrastructural digital images. To estimate inter- and intra-reader concordance of this descriptor-based approach, data from 12 pathologists (eight NEPTUNE and four non-NEPTUNE) with experience from training to 30 years were collected. A descriptor reference manual was generated and a webinar-based protocol for consensus/cross-training implemented. Intra-reader concordance for 51 glomerular descriptors was evaluated on jpeg images by seven NEPTUNE pathologists scoring 131 glomeruli three times (Tests I, II, and III), each test following a consensus webinar review. Inter-reader concordance of glomerular descriptors was evaluated in 315 glomeruli by all pathologists; interstitial fibrosis and tubular atrophy (244 cases, whole-slide images) and four ultrastructural podocyte descriptors (178 cases, jpeg images) were evaluated once by six and five pathologists, respectively. Cohen's kappa for inter-reader concordance for 48/51 glomerular descriptors with sufficient observations was moderate (0.40

Nanoparticle surface characterization and clustering through concentration-dependent surface adsorption modeling.

PubMed

Chen, Ran; Zhang, Yuntao; Sahneh, Faryad Darabi; Scoglio, Caterina M; Wohlleben, Wendel; Haase, Andrea; Monteiro-Riviere, Nancy A; Riviere, Jim E

2014-09-23

Quantitative characterization of nanoparticle interactions with their surrounding environment is vital for safe nanotechnological development and standardization. A recent quantitative measure, the biological surface adsorption index (BSAI), has demonstrated promising applications in nanomaterial surface characterization and biological/environmental prediction. This paper further advances the approach beyond the application of five descriptors in the original BSAI to address the concentration dependence of the descriptors, enabling better prediction of the adsorption profile and more accurate categorization of nanomaterials based on their surface properties. Statistical analysis on the obtained adsorption data was performed based on three different models: the original BSAI, a concentration-dependent polynomial model, and an infinite dilution model. These advancements in BSAI modeling showed a promising development in the application of quantitative predictive modeling in biological applications, nanomedicine, and environmental safety assessment of nanomaterials.

Structure-Activity Relationships for Rates of Aromatic Amine Oxidation by Manganese Dioxide

DOE PAGES

Salter-Blanc, Alexandra J.; Bylaska, Eric J.; Lyon, Molly A.; ...

2016-04-13

New energetic compounds are designed to minimize their potential environmental impacts, which includes their transformation and the fate and effects of their transformation products. The nitro groups of energetic compounds are readily reduced to amines, and the resulting aromatic amines are subject to oxidation and coupling reactions. Manganese dioxide (MnO 2) is a common environmental oxidant and model system for kinetic studies of aromatic amine oxidation. Here in this study, a training set of new and previously reported kinetic data for the oxidation of model and energetic-derived aromatic amines was assembled and subjected to correlation analysis against descriptor variables that ranged from general purpose [Hammettmore » $$\\sigma$$ constants ($$\\sigma^-$$), pK as of the amines, and energies of the highest occupied molecular orbital (E HOMO)] to specific for the likely rate-limiting step [one-electron oxidation potentials (E ox)]. The selection of calculated descriptors (pK a), E HOMO, and E ox) was based on validation with experimental data. All of the correlations gave satisfactory quantitative structure-activity relationships (QSARs), but they improved with the specificity of the descriptor. The scope of correlation analysis was extended beyond MnO 2 to include literature data on aromatic amine oxidation by other environmentally relevant oxidants (ozone, chlorine dioxide, and phosphate and carbonate radicals) by correlating relative rate constants (normalized to 4-chloroaniline) to E HOMO (calculated with a modest level of theory).« less

Structure-Activity Relationships for Rates of Aromatic Amine Oxidation by Manganese Dioxide

DOE Office of Scientific and Technical Information (OSTI.GOV)

Salter-Blanc, Alexandra J.; Bylaska, Eric J.; Lyon, Molly A.

New energetic compounds are designed to minimize their potential environmental impacts, which includes their transformation and the fate and effects of their transformation products. The nitro groups of energetic compounds are readily reduced to amines, and the resulting aromatic amines are subject to oxidation and coupling reactions. Manganese dioxide (MnO 2) is a common environmental oxidant and model system for kinetic studies of aromatic amine oxidation. Here in this study, a training set of new and previously reported kinetic data for the oxidation of model and energetic-derived aromatic amines was assembled and subjected to correlation analysis against descriptor variables that ranged from general purpose [Hammettmore » $$\\sigma$$ constants ($$\\sigma^-$$), pK as of the amines, and energies of the highest occupied molecular orbital (E HOMO)] to specific for the likely rate-limiting step [one-electron oxidation potentials (E ox)]. The selection of calculated descriptors (pK a), E HOMO, and E ox) was based on validation with experimental data. All of the correlations gave satisfactory quantitative structure-activity relationships (QSARs), but they improved with the specificity of the descriptor. The scope of correlation analysis was extended beyond MnO 2 to include literature data on aromatic amine oxidation by other environmentally relevant oxidants (ozone, chlorine dioxide, and phosphate and carbonate radicals) by correlating relative rate constants (normalized to 4-chloroaniline) to E HOMO (calculated with a modest level of theory).« less

Towards a metadata scheme for the description of materials - the description of microstructures

NASA Astrophysics Data System (ADS)

Schmitz, Georg J.; Böttger, Bernd; Apel, Markus; Eiken, Janin; Laschet, Gottfried; Altenfeld, Ralph; Berger, Ralf; Boussinot, Guillaume; Viardin, Alexandre

2016-01-01

The property of any material is essentially determined by its microstructure. Numerical models are increasingly the focus of modern engineering as helpful tools for tailoring and optimization of custom-designed microstructures by suitable processing and alloy design. A huge variety of software tools is available to predict various microstructural aspects for different materials. In the general frame of an integrated computational materials engineering (ICME) approach, these microstructure models provide the link between models operating at the atomistic or electronic scales, and models operating on the macroscopic scale of the component and its processing. In view of an improved interoperability of all these different tools it is highly desirable to establish a standardized nomenclature and methodology for the exchange of microstructure data. The scope of this article is to provide a comprehensive system of metadata descriptors for the description of a 3D microstructure. The presented descriptors are limited to a mere geometric description of a static microstructure and have to be complemented by further descriptors, e.g. for properties, numerical representations, kinetic data, and others in the future. Further attributes to each descriptor, e.g. on data origin, data uncertainty, and data validity range are being defined in ongoing work. The proposed descriptors are intended to be independent of any specific numerical representation. The descriptors defined in this article may serve as a first basis for standardization and will simplify the data exchange between different numerical models, as well as promote the integration of experimental data into numerical models of microstructures. An HDF5 template data file for a simple, three phase Al-Cu microstructure being based on the defined descriptors complements this article.

Towards a metadata scheme for the description of materials - the description of microstructures.

PubMed

Schmitz, Georg J; Böttger, Bernd; Apel, Markus; Eiken, Janin; Laschet, Gottfried; Altenfeld, Ralph; Berger, Ralf; Boussinot, Guillaume; Viardin, Alexandre

2016-01-01

The property of any material is essentially determined by its microstructure. Numerical models are increasingly the focus of modern engineering as helpful tools for tailoring and optimization of custom-designed microstructures by suitable processing and alloy design. A huge variety of software tools is available to predict various microstructural aspects for different materials. In the general frame of an integrated computational materials engineering (ICME) approach, these microstructure models provide the link between models operating at the atomistic or electronic scales, and models operating on the macroscopic scale of the component and its processing. In view of an improved interoperability of all these different tools it is highly desirable to establish a standardized nomenclature and methodology for the exchange of microstructure data. The scope of this article is to provide a comprehensive system of metadata descriptors for the description of a 3D microstructure. The presented descriptors are limited to a mere geometric description of a static microstructure and have to be complemented by further descriptors, e.g. for properties, numerical representations, kinetic data, and others in the future. Further attributes to each descriptor, e.g. on data origin, data uncertainty, and data validity range are being defined in ongoing work. The proposed descriptors are intended to be independent of any specific numerical representation. The descriptors defined in this article may serve as a first basis for standardization and will simplify the data exchange between different numerical models, as well as promote the integration of experimental data into numerical models of microstructures. An HDF5 template data file for a simple, three phase Al-Cu microstructure being based on the defined descriptors complements this article.

Mobile visual object identification: from SIFT-BoF-RANSAC to Sketchprint

NASA Astrophysics Data System (ADS)

Voloshynovskiy, Sviatoslav; Diephuis, Maurits; Holotyak, Taras

2015-03-01

Mobile object identification based on its visual features find many applications in the interaction with physical objects and security. Discriminative and robust content representation plays a central role in object and content identification. Complex post-processing methods are used to compress descriptors and their geometrical information, aggregate them into more compact and discriminative representations and finally re-rank the results based on the similarity geometries of descriptors. Unfortunately, most of the existing descriptors are not very robust and discriminative once applied to the various contend such as real images, text or noise-like microstructures next to requiring at least 500-1'000 descriptors per image for reliable identification. At the same time, the geometric re-ranking procedures are still too complex to be applied to the numerous candidates obtained from the feature similarity based search only. This restricts that list of candidates to be less than 1'000 which obviously causes a higher probability of miss. In addition, the security and privacy of content representation has become a hot research topic in multimedia and security communities. In this paper, we introduce a new framework for non- local content representation based on SketchPrint descriptors. It extends the properties of local descriptors to a more informative and discriminative, yet geometrically invariant content representation. In particular it allows images to be compactly represented by 100 SketchPrint descriptors without being fully dependent on re-ranking methods. We consider several use cases, applying SketchPrint descriptors to natural images, text documents, packages and micro-structures and compare them with the traditional local descriptors.

Deep Learning for Lowtextured Image Matching

NASA Astrophysics Data System (ADS)

Kniaz, V. V.; Fedorenko, V. V.; Fomin, N. A.

2018-05-01

Low-textured objects pose challenges for an automatic 3D model reconstruction. Such objects are common in archeological applications of photogrammetry. Most of the common feature point descriptors fail to match local patches in featureless regions of an object. Hence, automatic documentation of the archeological process using Structure from Motion (SfM) methods is challenging. Nevertheless, such documentation is possible with the aid of a human operator. Deep learning-based descriptors have outperformed most of common feature point descriptors recently. This paper is focused on the development of a new Wide Image Zone Adaptive Robust feature Descriptor (WIZARD) based on the deep learning. We use a convolutional auto-encoder to compress discriminative features of a local path into a descriptor code. We build a codebook to perform point matching on multiple images. The matching is performed using the nearest neighbor search and a modified voting algorithm. We present a new "Multi-view Amphora" (Amphora) dataset for evaluation of point matching algorithms. The dataset includes images of an Ancient Greek vase found at Taman Peninsula in Southern Russia. The dataset provides color images, a ground truth 3D model, and a ground truth optical flow. We evaluated the WIZARD descriptor on the "Amphora" dataset to show that it outperforms the SIFT and SURF descriptors on the complex patch pairs.

Environmental assessment in health care organizations.

PubMed

Romero, Isabel; Carnero, María Carmen

2017-12-22

The aim of this research is to design a multi-criteria model for environmental assessment of health care organizations. This is a model which guarantees the objectivity of the results obtained, is easy to apply, and incorporates a series of criteria, and their corresponding descriptors, relevant to the internal environmental auditing processes of the hospital. Furthermore, judgments were given by three experts from the areas of health, the environment, and multi-criteria decision techniques. From the values assigned, geometric means were calculated, giving weightings for the criteria of the model. This innovative model is intended for application within a continuous improvement process. A practical case from a Spanish hospital is included at the end. Information contained in the sustainability report provided the data needed to apply the model. The example contains all the criteria previously defined in the model. The results obtained show that the best-satisfied criteria are those related to energy consumption, generation of hazardous waste, legal matters, environmental sensitivity of staff, patients and others, and the environmental management of suppliers. On the other hand, those areas returning poor results are control of atmospheric emissions, increase in consumption of renewable energies, and the logistics of waste produced. It is recommended that steps be taken to correct these deficiencies, thus leading to an acceptable increase in the sustainability of the hospital.

Relationship between reaction rate constants of organic pollutants and their molecular descriptors during Fenton oxidation and in situ formed ferric-oxyhydroxides.

PubMed

Jia, Lijuan; Shen, Zhemin; Su, Pingru

2016-05-01

Fenton oxidation is a promising water treatment method to degrade organic pollutants. In this study, 30 different organic compounds were selected and their reaction rate constants (k) were determined for the Fenton oxidation process. Gaussian09 and Material Studio software sets were used to carry out calculations and obtain values of 10 different molecular descriptors for each studied compound. Ferric-oxyhydroxide coagulation experiments were conducted to determine the coagulation percentage. Based upon the adsorption capacity, all of the investigated organic compounds were divided into two groups (Group A and Group B). The percentage adsorption of organic compounds in Group A was less than 15% (wt./wt.) and that in the Group B was higher than 15% (wt./wt.). For Group A, removal of the compounds by oxidation was the dominant process while for Group B, removal by both oxidation and coagulation (as a synergistic process) took place. Results showed that the relationship between the rate constants (k values) and the molecular descriptors of Group A was more pronounced than for Group B compounds. For the oxidation-dominated process, EHOMO and Fukui indices (f(0)x, f(-)x, f(+)x) were the most significant factors. The influence of bond order was more significant for the synergistic process of oxidation and coagulation than for the oxidation-dominated process. The influences of all other molecular descriptors on the synergistic process were weaker than on the oxidation-dominated process. Copyright © 2015. Published by Elsevier B.V.

Temperature and relative humidity influence the ripening descriptors of Camembert-type cheeses throughout ripening.

PubMed

Leclercq-Perlat, M-N; Sicard, M; Perrot, N; Trelea, I C; Picque, D; Corrieu, G

2015-02-01

Ripening descriptors are the main factors that determine consumers' preferences of soft cheeses. Six descriptors were defined to represent the sensory changes in Camembert cheeses: Penicillium camemberti appearance, cheese odor and rind color, creamy underrind thickness and consistency, and core hardness. To evaluate the effects of the main process parameters on these descriptors, Camembert cheeses were ripened under different temperatures (8, 12, and 16°C) and relative humidity (RH; 88, 92, and 98%). The sensory descriptors were highly dependent on the temperature and RH used throughout ripening in a ripening chamber. All sensory descriptor changes could be explained by microorganism growth, pH, carbon substrate metabolism, and cheese moisture, as well as by microbial enzymatic activities. On d 40, at 8°C and 88% RH, all sensory descriptors scored the worst: the cheese was too dry, its odor and its color were similar to those of the unripe cheese, the underrind was driest, and the core was hardest. At 16°C and 98% RH, the odor was strongly ammonia and the color was dark brown, and the creamy underrind represented the entire thickness of the cheese but was completely runny, descriptors indicative of an over ripened cheese. Statistical analysis showed that the best ripening conditions to achieve an optimum balance between cheese sensory qualities and marketability were 13±1°C and 94±1% RH. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Ligand Electron Density Shape Recognition Using 3D Zernike Descriptors

NASA Astrophysics Data System (ADS)

Gunasekaran, Prasad; Grandison, Scott; Cowtan, Kevin; Mak, Lora; Lawson, David M.; Morris, Richard J.

We present a novel approach to crystallographic ligand density interpretation based on Zernike shape descriptors. Electron density for a bound ligand is expanded in an orthogonal polynomial series (3D Zernike polynomials) and the coefficients from this expansion are employed to construct rotation-invariant descriptors. These descriptors can be compared highly efficiently against large databases of descriptors computed from other molecules. In this manuscript we describe this process and show initial results from an electron density interpretation study on a dataset containing over a hundred OMIT maps. We could identify the correct ligand as the first hit in about 30 % of the cases, within the top five in a further 30 % of the cases, and giving rise to an 80 % probability of getting the correct ligand within the top ten matches. In all but a few examples, the top hit was highly similar to the correct ligand in both shape and chemistry. Further extensions and intrinsic limitations of the method are discussed.

An orientation sensitive approach in biomolecule interaction quantitative structure-activity relationship modeling and its application in ion-exchange chromatography.

PubMed

Kittelmann, Jörg; Lang, Katharina M H; Ottens, Marcel; Hubbuch, Jürgen

2017-01-27

Quantitative structure-activity relationship (QSAR) modeling for prediction of biomolecule parameters has become an established technique in chromatographic purification process design. Unfortunately available descriptor sets fail to describe the orientation of biomolecules and the effects of ionic strength in the mobile phase on the interaction with the stationary phase. The literature describes several special descriptors used for chromatographic retention modeling, all of these do not describe the screening of electrostatic potential by the mobile phase in use. In this work we introduce two new approaches of descriptor calculations, namely surface patches and plane projection, which capture an oriented binding to charged surfaces and steric hindrance of the interaction with chromatographic ligands with regard to electrostatic potential screening by mobile phase ions. We present the use of the developed descriptor sets for predictive modeling of Langmuir isotherms for proteins at different pH values between pH 5 and 10 and varying ionic strength in the range of 10-100mM. The resulting model has a high correlation of calculated descriptors and experimental results, with a coefficient of determination of 0.82 and a predictive coefficient of determination of 0.92 for unknown molecular structures and conditions. The agreement of calculated molecular interaction orientations with both, experimental results as well as molecular dynamic simulations from literature is shown. The developed descriptors provide the means for improved QSAR models of chromatographic processes, as they reflect the complex interactions of biomolecules with chromatographic phases. Copyright © 2016 Elsevier B.V. All rights reserved.

Innovative design method of automobile profile based on Fourier descriptor

NASA Astrophysics Data System (ADS)

Gao, Shuyong; Fu, Chaoxing; Xia, Fan; Shen, Wei

2017-10-01

Aiming at the innovation of the contours of automobile side, this paper presents an innovative design method of vehicle side profile based on Fourier descriptor. The design flow of this design method is: pre-processing, coordinate extraction, standardization, discrete Fourier transform, simplified Fourier descriptor, exchange descriptor innovation, inverse Fourier transform to get the outline of innovative design. Innovative concepts of the innovative methods of gene exchange among species and the innovative methods of gene exchange among different species are presented, and the contours of the innovative design are obtained separately. A three-dimensional model of a car is obtained by referring to the profile curve which is obtained by exchanging xenogeneic genes. The feasibility of the method proposed in this paper is verified by various aspects.

Fingerprint Identification Using SIFT-Based Minutia Descriptors and Improved All Descriptor-Pair Matching

PubMed Central

Zhou, Ru; Zhong, Dexing; Han, Jiuqiang

2013-01-01

The performance of conventional minutiae-based fingerprint authentication algorithms degrades significantly when dealing with low quality fingerprints with lots of cuts or scratches. A similar degradation of the minutiae-based algorithms is observed when small overlapping areas appear because of the quite narrow width of the sensors. Based on the detection of minutiae, Scale Invariant Feature Transformation (SIFT) descriptors are employed to fulfill verification tasks in the above difficult scenarios. However, the original SIFT algorithm is not suitable for fingerprint because of: (1) the similar patterns of parallel ridges; and (2) high computational resource consumption. To enhance the efficiency and effectiveness of the algorithm for fingerprint verification, we propose a SIFT-based Minutia Descriptor (SMD) to improve the SIFT algorithm through image processing, descriptor extraction and matcher. A two-step fast matcher, named improved All Descriptor-Pair Matching (iADM), is also proposed to implement the 1:N verifications in real-time. Fingerprint Identification using SMD and iADM (FISiA) achieved a significant improvement with respect to accuracy in representative databases compared with the conventional minutiae-based method. The speed of FISiA also can meet real-time requirements. PMID:23467056

Retro-regression--another important multivariate regression improvement.

PubMed

Randić, M

2001-01-01

We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA.

QSAR STUDY OF THE REDUCTION OF NITROAROMATICS BY FE (II) SPECIES

EPA Science Inventory

The development of predictive models for the reductive transformation of nitroaromatics requires further clarification of the effect of environmentally relevant variables on reaction kinetics and the identification of readily available molecular descriptors for calculating reacti...

Essential Set of Molecular Descriptors for ADME Prediction in Drug and Environmental Chemical Space

EPA Science Inventory

Historically, the disciplines of pharmacology and toxicology have embraced quantitative structure-activity relationships (QSAR) and quantitative structure-property relationships (QSPR) to predict ADME properties or biological activities of untested chemicals. The question arises ...

Arabidopsis phenotyping through Geometric Morphometrics.

PubMed

Manacorda, Carlos A; Asurmendi, Sebastian

2018-06-18

Recently, much technical progress was achieved in the field of plant phenotyping. High-throughput platforms and the development of improved algorithms for rosette image segmentation make it now possible to extract shape and size parameters for genetic, physiological and environmental studies on a large scale. The development of low-cost phenotyping platforms and freeware resources make it possible to widely expand phenotypic analysis tools for Arabidopsis. However, objective descriptors of shape parameters that could be used independently of platform and segmentation software used are still lacking and shape descriptions still rely on ad hoc or even sometimes contradictory descriptors, which could make comparisons difficult and perhaps inaccurate. Modern geometric morphometrics is a family of methods in quantitative biology proposed to be the main source of data and analytical tools in the emerging field of phenomics studies. Based on the location of landmarks (corresponding points) over imaged specimens and by combining geometry, multivariate analysis and powerful statistical techniques, these tools offer the possibility to reproducibly and accurately account for shape variations amongst groups and measure them in shape distance units. Here, a particular scheme of landmarks placement on Arabidopsis rosette images is proposed to study shape variation in the case of viral infection processes. Shape differences between controls and infected plants are quantified throughout the infectious process and visualized. Quantitative comparisons between two unrelated ssRNA+ viruses are shown and reproducibility issues are assessed. Combined with the newest automated platforms and plant segmentation procedures, geometric morphometric tools could boost phenotypic features extraction and processing in an objective, reproducible manner.

Language and the pain experience.

PubMed

Wilson, Dianne; Williams, Marie; Butler, David

2009-03-01

People in persistent pain have been reported to pay increased attention to specific words or descriptors of pain. The amount of attention paid to pain or cues for pain (such as pain descriptors), has been shown to be a major factor in the modulation of persistent pain. This relationship suggests the possibility that language may have a role both in understanding and managing the persistent pain experience. The aim of this paper is to describe current models of neuromatrices for pain and language, consider the role of attention in persistent pain states and highlight discrepancies, in previous studies based on the McGill Pain Questionnaire (MPQ), of the role of attention on pain descriptors. The existence of a pain neuromatrix originally proposed by Melzack (1990) has been supported by emerging technologies. Similar technologies have recently allowed identification of multiple areas of involvement for the processing of auditory input and the construction of language. As with the construction of pain, this neuromatrix for speech and language may intersect with neural systems for broader cognitive functions such as attention, memory and emotion. A systematic search was undertaken to identify experimental or review studies, which specifically investigated the role of attention on pain descriptors (as cues for pain) in persistent pain patients. A total of 99 articles were retrieved from six databases, with 66 articles meeting the inclusion criteria. After duplicated articles were eliminated, the remaining 41 articles were reviewed in order to support a link between persistent pain, pain descriptors and attention. This review revealed a diverse range of specific pain descriptors, the majority of which were derived from the MPQ. Increased attention to pain descriptors was consistently reported to be associated with emotional state as well as being a significant factor in maintaining persistent pain. However, attempts to investigate the attentional bias of specific pain descriptors highlighted discrepancies between the studies. As well as the diversity of pain descriptors used in studies, they were inconsistently categorized into domains of pain. A lack of consistent bias towards certain pain descriptors was observed, and may be explained simply by the fact that the words provided are not those which subjects themselves would use. These findings suggest that the multidimensional and individual nature of the persistent pain experience may not be adequately explained by pain questionnaires such as the MPQ. Personalized pain descriptors may communicate the pain experience more appropriately, but may also contribute to an increased sensitivity of cortical pain processing areas by capturing increased attention for that individual. The language used as part of communication between therapists and people with persistent pain may provide an, as yet, unexplored adjunct strategy in management. Copyright (c) 2008 John Wiley & Sons, Ltd.

Using probabilistic model as feature descriptor on a smartphone device for autonomous navigation of unmanned ground vehicles

NASA Astrophysics Data System (ADS)

Desai, Alok; Lee, Dah-Jye

2013-12-01

There has been significant research on the development of feature descriptors in the past few years. Most of them do not emphasize real-time applications. This paper presents the development of an affine invariant feature descriptor for low resource applications such as UAV and UGV that are equipped with an embedded system with a small microprocessor, a field programmable gate array (FPGA), or a smart phone device. UAV and UGV have proven suitable for many promising applications such as unknown environment exploration, search and rescue operations. These applications required on board image processing for obstacle detection, avoidance and navigation. All these real-time vision applications require a camera to grab images and match features using a feature descriptor. A good feature descriptor will uniquely describe a feature point thus allowing it to be correctly identified and matched with its corresponding feature point in another image. A few feature description algorithms are available for a resource limited system. They either require too much of the device's resource or too much simplification on the algorithm, which results in reduction in performance. This research is aimed at meeting the needs of these systems without sacrificing accuracy. This paper introduces a new feature descriptor called PRObabilistic model (PRO) for UGV navigation applications. It is a compact and efficient binary descriptor that is hardware-friendly and easy for implementation.

Chemically Aware Model Builder (camb): an R package for property and bioactivity modelling of small molecules.

PubMed

Murrell, Daniel S; Cortes-Ciriano, Isidro; van Westen, Gerard J P; Stott, Ian P; Bender, Andreas; Malliavin, Thérèse E; Glen, Robert C

2015-01-01

In silico predictive models have proved to be valuable for the optimisation of compound potency, selectivity and safety profiles in the drug discovery process. camb is an R package that provides an environment for the rapid generation of quantitative Structure-Property and Structure-Activity models for small molecules (including QSAR, QSPR, QSAM, PCM) and is aimed at both advanced and beginner R users. camb's capabilities include the standardisation of chemical structure representation, computation of 905 one-dimensional and 14 fingerprint type descriptors for small molecules, 8 types of amino acid descriptors, 13 whole protein sequence descriptors, filtering methods for feature selection, generation of predictive models (using an interface to the R package caret), as well as techniques to create model ensembles using techniques from the R package caretEnsemble). Results can be visualised through high-quality, customisable plots (R package ggplot2). Overall, camb constitutes an open-source framework to perform the following steps: (1) compound standardisation, (2) molecular and protein descriptor calculation, (3) descriptor pre-processing and model training, visualisation and validation, and (4) bioactivity/property prediction for new molecules. camb aims to speed model generation, in order to provide reproducibility and tests of robustness. QSPR and proteochemometric case studies are included which demonstrate camb's application.Graphical abstractFrom compounds and data to models: a complete model building workflow in one package.

Cheminformatic Analysis of the US EPA ToxCast Chemical Library

EPA Science Inventory

The ToxCast project is employing high throughput screening (HTS) technologies, along with chemical descriptors and computational models, to develop approaches for screening and prioritizing environmental chemicals for further toxicity testing. ToxCast Phase I generated HTS data f...

Genotype by environment (climate) interaction improves genomic prediction for production traits in US Holstein cattle.

PubMed

Tiezzi, F; de Los Campos, G; Parker Gaddis, K L; Maltecca, C

2017-03-01

Genotype by environment interaction (G × E) in dairy cattle productive traits has been shown to exist, but current genetic evaluation methods do not take this component into account. As several environmental descriptors (e.g., climate, farming system) are known to vary within the United States, not accounting for the G × E could lead to reranking of bulls and loss in genetic gain. Using test-day records on milk yield, somatic cell score, fat, and protein percentage from all over the United States, we computed within herd-year-season daughter yield deviations for 1,087 Holstein bulls and regressed them on genetic and environmental information to estimate variance components and to assess prediction accuracy. Genomic information was obtained from a 50k SNP marker panel. Environmental effect inputs included herd (160 levels), geographical region (7 levels), geographical location (2 variables), climate information (7 variables), and management conditions of the herds (16 total variables divided in 4 subgroups). For each set of environmental descriptors, environmental, genomic, and G × E components were sequentially fitted. Variance components estimates confirmed the presence of G × E on milk yield, with its effect being larger than main genetic effect and the environmental effect for some models. Conversely, G × E was moderate for somatic cell score and small for milk composition. Genotype by environment interaction, when included, partially eroded the genomic effect (as compared with the models where G × E was not included), suggesting that the genomic variance could at least in part be attributed to G × E not appropriately accounted for. Model predictive ability was assessed using 3 cross-validation schemes (new bulls, incomplete progeny test, and new environmental conditions), and performance was compared with a reference model including only the main genomic effect. In each scenario, at least 1 of the models including G × E was able to perform better than the reference model, although it was not possible to find the overall best-performing model that included the same set of environmental descriptors. In general, the methodology used is promising in accounting for G × E in genomic predictions, but challenges exist in identifying a unique set of covariates capable of describing the entire variety of environments. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Adaptation of EVIAVE methodology for monitoring and follow-up when evaluating the environmental impact of landfills

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arrieta, Gabriela, E-mail: tonina1903@hotmail.com; Requena, Ignacio, E-mail: requena@decsai.ugr.es; Toro, Javier, E-mail: jjtoroca@unal.edu.co

Treatment and final disposal of Municipal Solid Waste can have a significant role in the generation of negative environmental impacts. As a prevention strategy, such activities are subjected to the process of Environmental Impact Assessment (EIA). Still, the follow-up of Environmental Management Plans or mitigation measures is limited, for one due to a lack of methodological approaches. In searching for possibilities, the University of Granada (Spain) developed a diagnostic methodology named EVIAVE, which allows one to quantify, by means of indexes, the environmental impact of landfills in view of their location and the conditions of exploitation. EVIAVE is applicable withinmore » the legal framework of the European Union and can be adapted to the environmental and legal conditions of other countries. This study entails its adaptation in Colombia, for the follow-up and control of the EIA process for landfills. Modifications involved inclusion of the environmental elements flora and fauna, and the evaluation of the environmental descriptors in agreement with the concept of vulnerability. The application of the modified EVIAVE in Colombian landfills allowed us to identify the elements affected by the operating conditions and maintenance. It may be concluded that this methodology is viable and effective for the follow-up and environmental control of EIA processes for landfills, and to analyze the associated risks, as it takes into account related environmental threats and vulnerabilities. - Highlights: • A modified methodology is used to monitor and follow-up environmental impacts in landfills. • The improved methodology includes the Vulnerability of Flora and Fauna to evaluate environmental impact of landfills. • The methodology serves to identify and evaluate the sources of risk generated in the construction and siting of landfills. • Environmental vulnerability indicators improve effectiveness of the control and follow-up phases of landfill management. • The follow-up of environmental management plans may help diminish the implementation gap in Environmental Impact Assessment.« less

Web-4D-QSAR: A web-based application to generate 4D-QSAR descriptors.

PubMed

Ataide Martins, João Paulo; Rougeth de Oliveira, Marco Antônio; Oliveira de Queiroz, Mário Sérgio

2018-06-05

A web-based application is developed to generate 4D-QSAR descriptors using the LQTA-QSAR methodology, based on molecular dynamics (MD) trajectories and topology information retrieved from the GROMACS package. The LQTAGrid module calculates the intermolecular interaction energies at each grid point, considering probes and all aligned conformations resulting from MD simulations. These interaction energies are the independent variables or descriptors employed in a QSAR analysis. A friendly front end web interface, built using the Django framework and Python programming language, integrates all steps of the LQTA-QSAR methodology in a way that is transparent to the user, and in the backend, GROMACS and LQTAGrid are executed to generate 4D-QSAR descriptors to be used later in the process of QSAR model building. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Preventing messaging queue deadlocks in a DMA environment

DOEpatents

Blocksome, Michael A; Chen, Dong; Gooding, Thomas; Heidelberger, Philip; Parker, Jeff

2014-01-14

Embodiments of the invention may be used to manage message queues in a parallel computing environment to prevent message queue deadlock. A direct memory access controller of a compute node may determine when a messaging queue is full. In response, the DMA may generate and interrupt. An interrupt handler may stop the DMA and swap all descriptors from the full messaging queue into a larger queue (or enlarge the original queue). The interrupt handler then restarts the DMA. Alternatively, the interrupt handler stops the DMA, allocates a memory block to hold queue data, and then moves descriptors from the full messaging queue into the allocated memory block. The interrupt handler then restarts the DMA. During a normal messaging advance cycle, a messaging manager attempts to inject the descriptors in the memory block into other messaging queues until the descriptors have all been processed.

The Marine Strategy Framework Directive and the ecosystem-based approach – pitfalls and solutions.

PubMed

Berg, Torsten; Fürhaupter, Karin; Teixeira, Heliana; Uusitalo, Laura; Zampoukas, Nikolaos

2015-07-15

The European Marine Strategy Framework Directive aims at good environmental status (GES) in marine waters, following an ecosystem-based approach, focused on 11 descriptors related to ecosystem features, human drivers and pressures. Furthermore, 29 subordinate criteria and 56 attributes are detailed in an EU Commission Decision. The analysis of the Decision and the associated operational indicators revealed ambiguity in the use of terms, such as indicator, impact and habitat and considerable overlap of indicators assigned to various descriptors and criteria. We suggest re-arrangement and elimination of redundant criteria and attributes avoiding double counting in the subsequent indicator synthesis, a clear distinction between pressure and state descriptors and addition of criteria on ecosystem services and functioning. Moreover, we suggest the precautionary principle should be followed for the management of pressures and an evidence-based approach for monitoring state as well as reaching and maintaining GES. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

A Universal 3D Voxel Descriptor for Solid-State Material Informatics with Deep Convolutional Neural Networks.

PubMed

Kajita, Seiji; Ohba, Nobuko; Jinnouchi, Ryosuke; Asahi, Ryoji

2017-12-05

Material informatics (MI) is a promising approach to liberate us from the time-consuming Edisonian (trial and error) process for material discoveries, driven by machine-learning algorithms. Several descriptors, which are encoded material features to feed computers, were proposed in the last few decades. Especially to solid systems, however, their insufficient representations of three dimensionality of field quantities such as electron distributions and local potentials have critically hindered broad and practical successes of the solid-state MI. We develop a simple, generic 3D voxel descriptor that compacts any field quantities, in such a suitable way to implement convolutional neural networks (CNNs). We examine the 3D voxel descriptor encoded from the electron distribution by a regression test with 680 oxides data. The present scheme outperforms other existing descriptors in the prediction of Hartree energies that are significantly relevant to the long-wavelength distribution of the valence electrons. The results indicate that this scheme can forecast any functionals of field quantities just by learning sufficient amount of data, if there is an explicit correlation between the target properties and field quantities. This 3D descriptor opens a way to import prominent CNNs-based algorithms of supervised, semi-supervised and reinforcement learnings into the solid-state MI.

Geotechnical Factors in the Dredgeability of Sediments. Report 1. Geotechnical Descriptors for Sediments to be Dredged

DTIC Science & Technology

1993-11-01

objectives of the work unit. executing dredging projects. The disparities increase risk factors and thus the cost of such SUMMARY: The study identified the...geologists, environmental engineers, biologists, estimators, dredging equipment manufacturers, and dredging contractor personnel have methods for...changed dramatically. A major increase has occurred in the level of contract dredging. Environmental concerns, the consequences of the oil embargo of

Designing a Quantitative Structure-Activity Relationship for the ...

EPA Pesticide Factsheets

Toxicokinetic models serve a vital role in risk assessment by bridging the gap between chemical exposure and potentially toxic endpoints. While intrinsic metabolic clearance rates have a strong impact on toxicokinetics, limited data is available for environmentally relevant chemicals including nearly 8000 chemicals tested for in vitro bioactivity in the Tox21 program. To address this gap, a quantitative structure-activity relationship (QSAR) for intrinsic metabolic clearance rate was developed to offer reliable in silico predictions for a diverse array of chemicals. Models were constructed with curated in vitro assay data for both pharmaceutical-like chemicals (ChEMBL database) and environmentally relevant chemicals (ToxCast screening) from human liver microsomes (2176 from ChEMBL) and human hepatocytes (757 from ChEMBL and 332 from ToxCast). Due to variability in the experimental data, a binned approach was utilized to classify metabolic rates. Machine learning algorithms, such as random forest and k-nearest neighbor, were coupled with open source molecular descriptors and fingerprints to provide reasonable estimates of intrinsic metabolic clearance rates. Applicability domains defined the optimal chemical space for predictions, which covered environmental chemicals well. A reduced set of informative descriptors (including relative charge and lipophilicity) and a mixed training set of pharmaceuticals and environmentally relevant chemicals provided the best intr

Informing the Human Plasma Protein Binding of ...

EPA Pesticide Factsheets

The free fraction of a xenobiotic in plasma (Fub) is an important determinant of chemical adsorption, distribution, metabolism, elimination, and toxicity, yet experimental plasma protein binding data is scarce for environmentally relevant chemicals. The presented work explores the merit of utilizing available pharmaceutical data to predict Fub for environmentally relevant chemicals via machine learning techniques. Quantitative structure-activity relationship (QSAR) models were constructed with k nearest neighbors (kNN), support vector machines (SVM), and random forest (RF) machine learning algorithms from a training set of 1045 pharmaceuticals. The models were then evaluated with independent test sets of pharmaceuticals (200 compounds) and environmentally relevant ToxCast chemicals (406 total, in two groups of 238 and 168 compounds). The selection of a minimal feature set of 10-15 2D molecular descriptors allowed for both informative feature interpretation and practical applicability domain assessment via a bounded box of descriptor ranges and principal component analysis. The diverse pharmaceutical and environmental chemical sets exhibit similarities in terms of chemical space (99-82% overlap), as well as comparable bias and variance in constructed learning curves. All the models exhibit significant predictability with mean absolute errors (MAE) in the range of 0.10-0.18 Fub. The models performed best for highly bound chemicals (MAE 0.07-0.12), neutrals (MAE 0

Health sciences descriptors in the brazilian speech-language and hearing science.

PubMed

Campanatti-Ostiz, Heliane; Andrade, Claudia Regina Furquim de

2010-01-01

Terminology in Speech-Language and Hearing Science. To propose a specific thesaurus about the Speech-Language and Hearing Science, for the English, Portuguese and Spanish languages, based on the existing keywords available on the Health Sciences Descriptors (DeCS). Methodology was based on the pilot study developed by Campanatti-Ostiz and Andrade; that had as a purpose to verify the methodological viability for the creation of a Speech-Language and Hearing Science category in the DeCS. The scientific journals selected for analyses of the titles, abstracts and keywords of all scientific articles were those in the field of the Speech-Language and Hearing Science, indexed on the SciELO. 1. Recovery of the Descriptors in the English language (Medical Subject Headings--MeSH); 2. Recovery and hierarchic organization of the descriptors in the Portuguese language was done (DeCS). The obtained data was analyzed as follows: descriptive analyses and relative relevance analyses of the DeCS areas. Based on the first analyses, we decided to select all 761 descriptors, with all the hierarchic numbers, independently of their occurrence (occurrence number--ON), and based on the second analyses, we decided to propose to exclude the less relevant areas and the exclusive DeCS areas. The proposal was finished with a total of 1676 occurrences of DeCS descriptors, distributed in the following areas: Anatomy; Diseases; Analytical, Diagnostic and Therapeutic Techniques and Equipments; Psychiatry and Psychology; Phenomena and Processes; Health Care. The presented proposal of a thesaurus contains the specific terminology of the Brazilian Speech-Language and Hearing Sciences and reflects the descriptors of the published scientific production. Being the DeCS a trilingual vocabulary (Portuguese, English and Spanish), the present descriptors organization proposition can be used in these three languages, allowing greater cultural interchange between different nations.

Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach

PubMed Central

Murat, Miraemiliana; Abu, Arpah; Yap, Hwa Jen; Yong, Kien-Thai

2017-01-01

Plants play a crucial role in foodstuff, medicine, industry, and environmental protection. The skill of recognising plants is very important in some applications, including conservation of endangered species and rehabilitation of lands after mining activities. However, it is a difficult task to identify plant species because it requires specialized knowledge. Developing an automated classification system for plant species is necessary and valuable since it can help specialists as well as the public in identifying plant species easily. Shape descriptors were applied on the myDAUN dataset that contains 45 tropical shrub species collected from the University of Malaya (UM), Malaysia. Based on literature review, this is the first study in the development of tropical shrub species image dataset and classification using a hybrid of leaf shape and machine learning approach. Four types of shape descriptors were used in this study namely morphological shape descriptors (MSD), Histogram of Oriented Gradients (HOG), Hu invariant moments (Hu) and Zernike moments (ZM). Single descriptor, as well as the combination of hybrid descriptors were tested and compared. The tropical shrub species are classified using six different classifiers, which are artificial neural network (ANN), random forest (RF), support vector machine (SVM), k-nearest neighbour (k-NN), linear discriminant analysis (LDA) and directed acyclic graph multiclass least squares twin support vector machine (DAG MLSTSVM). In addition, three types of feature selection methods were tested in the myDAUN dataset, Relief, Correlation-based feature selection (CFS) and Pearson’s coefficient correlation (PCC). The well-known Flavia dataset and Swedish Leaf dataset were used as the validation dataset on the proposed methods. The results showed that the hybrid of all descriptors of ANN outperformed the other classifiers with an average classification accuracy of 98.23% for the myDAUN dataset, 95.25% for the Flavia dataset and 99.89% for the Swedish Leaf dataset. In addition, the Relief feature selection method achieved the highest classification accuracy of 98.13% after 80 (or 60%) of the original features were reduced, from 133 to 53 descriptors in the myDAUN dataset with the reduction in computational time. Subsequently, the hybridisation of four descriptors gave the best results compared to others. It is proven that the combination MSD and HOG were good enough for tropical shrubs species classification. Hu and ZM descriptors also improved the accuracy in tropical shrubs species classification in terms of invariant to translation, rotation and scale. ANN outperformed the others for tropical shrub species classification in this study. Feature selection methods can be used in the classification of tropical shrub species, as the comparable results could be obtained with the reduced descriptors and reduced in computational time and cost. PMID:28924506

Automated classification of tropical shrub species: a hybrid of leaf shape and machine learning approach.

PubMed

Murat, Miraemiliana; Chang, Siow-Wee; Abu, Arpah; Yap, Hwa Jen; Yong, Kien-Thai

2017-01-01

Plants play a crucial role in foodstuff, medicine, industry, and environmental protection. The skill of recognising plants is very important in some applications, including conservation of endangered species and rehabilitation of lands after mining activities. However, it is a difficult task to identify plant species because it requires specialized knowledge. Developing an automated classification system for plant species is necessary and valuable since it can help specialists as well as the public in identifying plant species easily. Shape descriptors were applied on the myDAUN dataset that contains 45 tropical shrub species collected from the University of Malaya (UM), Malaysia. Based on literature review, this is the first study in the development of tropical shrub species image dataset and classification using a hybrid of leaf shape and machine learning approach. Four types of shape descriptors were used in this study namely morphological shape descriptors (MSD), Histogram of Oriented Gradients (HOG), Hu invariant moments (Hu) and Zernike moments (ZM). Single descriptor, as well as the combination of hybrid descriptors were tested and compared. The tropical shrub species are classified using six different classifiers, which are artificial neural network (ANN), random forest (RF), support vector machine (SVM), k-nearest neighbour (k-NN), linear discriminant analysis (LDA) and directed acyclic graph multiclass least squares twin support vector machine (DAG MLSTSVM). In addition, three types of feature selection methods were tested in the myDAUN dataset, Relief, Correlation-based feature selection (CFS) and Pearson's coefficient correlation (PCC). The well-known Flavia dataset and Swedish Leaf dataset were used as the validation dataset on the proposed methods. The results showed that the hybrid of all descriptors of ANN outperformed the other classifiers with an average classification accuracy of 98.23% for the myDAUN dataset, 95.25% for the Flavia dataset and 99.89% for the Swedish Leaf dataset. In addition, the Relief feature selection method achieved the highest classification accuracy of 98.13% after 80 (or 60%) of the original features were reduced, from 133 to 53 descriptors in the myDAUN dataset with the reduction in computational time. Subsequently, the hybridisation of four descriptors gave the best results compared to others. It is proven that the combination MSD and HOG were good enough for tropical shrubs species classification. Hu and ZM descriptors also improved the accuracy in tropical shrubs species classification in terms of invariant to translation, rotation and scale. ANN outperformed the others for tropical shrub species classification in this study. Feature selection methods can be used in the classification of tropical shrub species, as the comparable results could be obtained with the reduced descriptors and reduced in computational time and cost.

Increasing available FIFO space to prevent messaging queue deadlocks in a DMA environment

DOEpatents

Blocksome, Michael A [Rochester, MN; Chen, Dong [Croton On Hudson, NY; Gooding, Thomas [Rochester, MN; Heidelberger, Philip [Cortlandt Manor, NY; Parker, Jeff [Rochester, MN

2012-02-07

Embodiments of the invention may be used to manage message queues in a parallel computing environment to prevent message queue deadlock. A direct memory access controller of a compute node may determine when a messaging queue is full. In response, the DMA may generate an interrupt. An interrupt handler may stop the DMA and swap all descriptors from the full messaging queue into a larger queue (or enlarge the original queue). The interrupt handler then restarts the DMA. Alternatively, the interrupt handler stops the DMA, allocates a memory block to hold queue data, and then moves descriptors from the full messaging queue into the allocated memory block. The interrupt handler then restarts the DMA. During a normal messaging advance cycle, a messaging manager attempts to inject the descriptors in the memory block into other messaging queues until the descriptors have all been processed.

Quantitative structure-retention relationships of polycyclic aromatic hydrocarbons gas-chromatographic retention indices.

PubMed

Drosos, Juan Carlos; Viola-Rhenals, Maricela; Vivas-Reyes, Ricardo

2010-06-25

Polycyclic aromatic compounds (PAHs) are of concern in environmental chemistry and toxicology. In the present work, a QSRR study was performed for 209 previously reported PAHs using quantum mechanics and other sources descriptors estimated by different approaches. The B3LYP/6-31G* level of theory was used for geometrical optimization and quantum mechanics related variables. A good linear relationship between gas-chromatographic retention index and electronic or topologic descriptors was found by stepwise linear regression analysis. The molecular polarizability (alpha) and the second order molecular connectivity Kier and Hall index ((2)chi) showed evidence of significant correlation with retention index by means of important squared coefficient of determination, (R(2)), values (R(2)=0.950 and 0.962, respectively). A one variable QSRR model is presented for each descriptor and both models demonstrates a significant predictive capacity established using the leave-many-out LMO (excluding 25% of rows) cross validation method's q(2) cross-validation coefficients q(2)(CV-LMO25%), (obtained q(2)(CV-LMO25%) 0.947 and 0.960, respectively). Furthermore, the physicochemical interpretation of selected descriptors allowed detailed explanation of the source of the observed statistical correlation. The model analysis suggests that only one descriptor is sufficient to establish a consistent retention index-structure relationship. Moderate or non-significant improve was observed for quantitative results or statistical validation parameters when introducing more terms in predictive equation. The one parameter QSRR proposed model offers a consistent scheme to predict chromatographic properties of PAHs compounds. Copyright 2010 Elsevier B.V. All rights reserved.

The link between descriptors 8 and 9 of the Marine Strategy Framework Directive: lessons learnt in Spain.

PubMed

Gago, J; Viñas, L; Besada, V; Bellas, J

2014-12-01

The aim of this note is to discuss the relevance of the interaction/integration of monitoring of contaminants for the protection of the marine environment and for human health safety (descriptors 8 and 9, respectively) within the Marine Strategy Framework Directive (MSFD). The identification of possible relations between contaminant levels in sediments and tissues of fish and other seafood, as well as the association of those levels to pollution sources, are major challenges for marine researchers. The Spanish initial assessment in the North-East Atlantic marine region was used as an example to show some gaps and loopholes when dealing with the relationship between descriptors 8 and 9. The main problem to deal with is that monitoring programmes intended for the assessment of marine environmental quality and for human health safety usually apply different approaches and methodologies, and even different tissues are analysed in some species (mainly fish). It is therefore recommended to make a profound revision of current sampling strategies, procedures and methodologies, including the selection of target species and tissues and to improve the traceability of samples of fish and other seafood for human consumption. On the other hand, despite the scope of descriptor 9 which is limited to commercially relevant species, this fact should not be an obstacle in the application of the 'ecosystem approach' within the MSFD. In order to appropriately solve these shortcomings, an information exchange system between authorities dealing with descriptors 8 and 9 should be strongly encouraged for the next steps of the MSFD's implementation.

The application of feature selection to the development of Gaussian process models for percutaneous absorption.

PubMed

Lam, Lun Tak; Sun, Yi; Davey, Neil; Adams, Rod; Prapopoulou, Maria; Brown, Marc B; Moss, Gary P

2010-06-01

The aim was to employ Gaussian processes to assess mathematically the nature of a skin permeability dataset and to employ these methods, particularly feature selection, to determine the key physicochemical descriptors which exert the most significant influence on percutaneous absorption, and to compare such models with established existing models. Gaussian processes, including automatic relevance detection (GPRARD) methods, were employed to develop models of percutaneous absorption that identified key physicochemical descriptors of percutaneous absorption. Using MatLab software, the statistical performance of these models was compared with single linear networks (SLN) and quantitative structure-permeability relationships (QSPRs). Feature selection methods were used to examine in more detail the physicochemical parameters used in this study. A range of statistical measures to determine model quality were used. The inherently nonlinear nature of the skin data set was confirmed. The Gaussian process regression (GPR) methods yielded predictive models that offered statistically significant improvements over SLN and QSPR models with regard to predictivity (where the rank order was: GPR > SLN > QSPR). Feature selection analysis determined that the best GPR models were those that contained log P, melting point and the number of hydrogen bond donor groups as significant descriptors. Further statistical analysis also found that great synergy existed between certain parameters. It suggested that a number of the descriptors employed were effectively interchangeable, thus questioning the use of models where discrete variables are output, usually in the form of an equation. The use of a nonlinear GPR method produced models with significantly improved predictivity, compared with SLN or QSPR models. Feature selection methods were able to provide important mechanistic information. However, it was also shown that significant synergy existed between certain parameters, and as such it was possible to interchange certain descriptors (i.e. molecular weight and melting point) without incurring a loss of model quality. Such synergy suggested that a model constructed from discrete terms in an equation may not be the most appropriate way of representing mechanistic understandings of skin absorption.

Predicting hepatotoxicity using ToxCast in vitro bioactivity and chemical structure

EPA Science Inventory

Background: The U.S. EPA ToxCastTM program is screening thousands of environmental chemicals for bioactivity using hundreds of high-throughput in vitro assays to build predictive models of toxicity. We represented chemicals based on bioactivity and chemical structure descriptors ...

Revealing chemophoric sites in organophosphorus insecticides through the MIA-QSPR modeling of soil sorption data.

PubMed

Daré, Joyce K; Silva, Cristina F; Freitas, Matheus P

2017-10-01

Soil sorption of insecticides employed in agriculture is an important parameter to probe the environmental fate of organic chemicals. Therefore, methods for the prediction of soil sorption of new agrochemical candidates, as well as for the rationalization of the molecular characteristics responsible for a given sorption profile, are extremely beneficial for the environment. A quantitative structure-property relationship method based on chemical structure images as molecular descriptors provided a reliable model for the soil sorption prediction of 24 widely used organophosphorus insecticides. By means of contour maps obtained from the partial least squares regression coefficients and the variable importance in projection scores, key molecular moieties were targeted for possible structural modification, in order to obtain novel and more environmentally friendly insecticide candidates. The image-based descriptors applied encode molecular arrangement, atoms connectivity, groups size, and polarity; consequently, the findings in this work cannot be achieved by a simple relationship with hydrophobicity, usually described by the octanol-water partition coefficient. Copyright © 2017 Elsevier Inc. All rights reserved.

Force majeure: Will climate change affect our ability to attain Good Environmental Status for marine biodiversity?

PubMed

Elliott, Michael; Borja, Ángel; McQuatters-Gollop, Abigail; Mazik, Krysia; Birchenough, Silvana; Andersen, Jesper H; Painting, Suzanne; Peck, Myron

2015-06-15

The EU Marine Strategy Framework Directive (MSFD) requires that Good Environmental Status (GEnS), is achieved for European seas by 2020. These may deviate from GEnS, its 11 Descriptors, targets and baselines, due to endogenic managed pressures (from activities within an area) and externally due to exogenic unmanaged pressures (e.g. climate change). Conceptual models detail the likely or perceived changes expected on marine biodiversity and GEnS Descriptors in the light of climate change. We emphasise that marine management has to accommodate 'shifting baselines' caused by climate change particularly during GEnS monitoring, assessment and management and 'unbounded boundaries' given the migration and dispersal of highly-mobile species. We suggest climate change may prevent GEnS being met, but Member States may rebut legal challenges by claiming that this is outside its control, force majeure or due to 'natural causes' (Article 14 of the MSFD). The analysis is relevant to management of other global seas. Copyright © 2015 Elsevier Ltd. All rights reserved.

Descriptors of natural thermal regimes in streams and their responsiveness to change in the Pacific Northwest of North America

Treesearch

Ivan Arismendi; Sherri L. Johnson; Jason B. Dunham; Roy Haggerty

2013-01-01

1. Temperature is a major driver of ecological processes in stream ecosystems, yet the dynamics of thermal regimes remain poorly described. Most work has focused on relatively simple descriptors that fail to capture the full range of conditions that characterise thermal regimes of streams across seasons or throughout the year.2. To more...

Integrating Biological and Chemical Data for Hepatotoxicity Prediction (SOT)

EPA Science Inventory

The U.S. EPA ToxCastTM program is screening thousands of environmental chemicals for bioactivity using hundreds of high-throughput in vitro assays to build predictive models of toxicity. A set of 677 chemicals were represented by 711 bioactivity descriptors (from ToxCast assays),...

Plant Identification Based on Leaf Midrib Cross-Section Images Using Fractal Descriptors.

PubMed

da Silva, Núbia Rosa; Florindo, João Batista; Gómez, María Cecilia; Rossatto, Davi Rodrigo; Kolb, Rosana Marta; Bruno, Odemir Martinez

2015-01-01

The correct identification of plants is a common necessity not only to researchers but also to the lay public. Recently, computational methods have been employed to facilitate this task, however, there are few studies front of the wide diversity of plants occurring in the world. This study proposes to analyse images obtained from cross-sections of leaf midrib using fractal descriptors. These descriptors are obtained from the fractal dimension of the object computed at a range of scales. In this way, they provide rich information regarding the spatial distribution of the analysed structure and, as a consequence, they measure the multiscale morphology of the object of interest. In Biology, such morphology is of great importance because it is related to evolutionary aspects and is successfully employed to characterize and discriminate among different biological structures. Here, the fractal descriptors are used to identify the species of plants based on the image of their leaves. A large number of samples are examined, being 606 leaf samples of 50 species from Brazilian flora. The results are compared to other imaging methods in the literature and demonstrate that fractal descriptors are precise and reliable in the taxonomic process of plant species identification.

In silico environmental chemical science: properties and processes from statistical and computational modelling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tratnyek, Paul G.; Bylaska, Eric J.; Weber, Eric J.

2017-01-01

Quantitative structure–activity relationships (QSARs) have long been used in the environmental sciences. More recently, molecular modeling and chemoinformatic methods have become widespread. These methods have the potential to expand and accelerate advances in environmental chemistry because they complement observational and experimental data with “in silico” results and analysis. The opportunities and challenges that arise at the intersection between statistical and theoretical in silico methods are most apparent in the context of properties that determine the environmental fate and effects of chemical contaminants (degradation rate constants, partition coefficients, toxicities, etc.). The main example of this is the calibration of QSARs usingmore » descriptor variable data calculated from molecular modeling, which can make QSARs more useful for predicting property data that are unavailable, but also can make them more powerful tools for diagnosis of fate determining pathways and mechanisms. Emerging opportunities for “in silico environmental chemical science” are to move beyond the calculation of specific chemical properties using statistical models and toward more fully in silico models, prediction of transformation pathways and products, incorporation of environmental factors into model predictions, integration of databases and predictive models into more comprehensive and efficient tools for exposure assessment, and extending the applicability of all the above from chemicals to biologicals and materials.« less

Constructive alignment of a research-informed teaching activity within an undergraduate diagnostic radiography curriculum: A reflection.

PubMed

Higgins, R; Hogg, P; Robinson, L

2017-09-01

To evaluate the learning experience of a level 5 (year 2) student cohort within a research-informed teaching (RiT) activity and to map findings against learning outcomes and level descriptors using constructive alignment. An online questionnaire was used to explore the level 5 student experience of a Research-informed Teaching (RiT) activity. Responses were retrospectively mapped against Framework for Higher Education Qualifications (FHEQ) level descriptors for level 5 using constructive alignment. Thirty one out of 46 level 5 students completed the questionnaire (67% response rate). Analysis of the questionnaire supported the integration of this RiT activity within the curriculum in terms of learning and research skill development by students. However, it was identified that this activity could be revised further to better align with level 5 descriptors and incorporate additional higher level cognitive processes. Learning outcomes for this RiT activity were constructively aligned with FHEQ level 5 descriptors. Recommendations are provided on how these could be further refined to ensure students undertake a more critical approach to the application of theory into practice. Discussion also considers how this process could be used to develop a similar RiT activity at level 6 (year 3). Copyright © 2016 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.

Fast human pose estimation using 3D Zernike descriptors

NASA Astrophysics Data System (ADS)

Berjón, Daniel; Morán, Francisco

2012-03-01

Markerless video-based human pose estimation algorithms face a high-dimensional problem that is frequently broken down into several lower-dimensional ones by estimating the pose of each limb separately. However, in order to do so they need to reliably locate the torso, for which they typically rely on time coherence and tracking algorithms. Their losing track usually results in catastrophic failure of the process, requiring human intervention and thus precluding their usage in real-time applications. We propose a very fast rough pose estimation scheme based on global shape descriptors built on 3D Zernike moments. Using an articulated model that we configure in many poses, a large database of descriptor/pose pairs can be computed off-line. Thus, the only steps that must be done on-line are the extraction of the descriptors for each input volume and a search against the database to get the most likely poses. While the result of such process is not a fine pose estimation, it can be useful to help more sophisticated algorithms to regain track or make more educated guesses when creating new particles in particle-filter-based tracking schemes. We have achieved a performance of about ten fps on a single computer using a database of about one million entries.

DMA engine for repeating communication patterns

DOEpatents

Chen, Dong; Gara, Alan G.; Giampapa, Mark E.; Heidelberger, Philip; Steinmacher-Burow, Burkhard; Vranas, Pavlos

2010-09-21

A parallel computer system is constructed as a network of interconnected compute nodes to operate a global message-passing application for performing communications across the network. Each of the compute nodes includes one or more individual processors with memories which run local instances of the global message-passing application operating at each compute node to carry out local processing operations independent of processing operations carried out at other compute nodes. Each compute node also includes a DMA engine constructed to interact with the application via Injection FIFO Metadata describing multiple Injection FIFOs where each Injection FIFO may containing an arbitrary number of message descriptors in order to process messages with a fixed processing overhead irrespective of the number of message descriptors included in the Injection FIFO.

Searching for Global Descriptors of Engineered Nanomaterial Fate and Transport in the Environment

PubMed Central

Nowack, Bernd

2012-01-01

CONSPECTUS Engineered nanomaterials (ENMs) are a new class of environmental pollutants. Researchers are beginning to debate whether new modeling paradigms and experimental tests to obtain model parameters are required for ENMs or if approaches for existing pollutants are robust enough to predict ENM distribution between environmental compartments. This Account outlines how experimental research can yield quantitative data for use in ENM fate and exposure models. We first review experimental testing approaches that are employed with ENMs. Then we compare and contrast ENMs against other pollutants. Finally, we summarize the findings and identify research needs that may yield global descriptors for ENMs that are suitable for use in fate and transport modeling. Over the past decade, researchers have made significant progress in understanding factors that influence the fate and transport of ENMs. In some cases researchers have developed approaches toward global descriptor models (experimental, conceptual, and quantitative). We suggest the following global descriptors for ENMs: octanol-water partition coefficients, solid-water partition coefficients, attachment coefficients, and rate constants describing reactions such as dissolution, sedimentation, and degradation. ENMs appear to accumulate at the octanol-water interface and readily interact with other interfaces, such as lipid-water interfaces. Batch experiments to investigate factors that influence retention of ENMs on solid phases are very promising. However ENMs probably do not behave in the same way as dissolved chemicals, and therefore researchers need to use measurement techniques and concepts more commonly associated with colloids. Despite several years of research with ENMs in column studies, available summaries tend to discuss the effects of ionic strength, pH, organic matter, ENM type, packing media, or other parameters qualitatively rather than reporting quantitative values, such as attachment efficiencies, that would facilitate comparison across studies. Only a few structure-activity relationships have been developed for ENMs so far, but such evaluations will facilitate the understanding of the reactivities of different forms of a single ENM. The establishment of predictive capabilities for ENMs in the environment would enable accurate exposure assessments that would assist in ENM risk management. Such information is also critical for understanding the ultimate disposition of ENMs and may provide a framework for improved engineering of nanomaterials that are more environmentally benign. PMID:22950943

Chemometric Methods and Theoretical Molecular Descriptors in Predictive QSAR Modeling of the Environmental Behavior of Organic Pollutants

NASA Astrophysics Data System (ADS)

Gramatica, Paola

This chapter surveys the QSAR modeling approaches (developed by the author's research group) for the validated prediction of environmental properties of organic pollutants. Various chemometric methods, based on different theoretical molecular descriptors, have been applied: explorative techniques (such as PCA for ranking, SOM for similarity analysis), modeling approaches by multiple-linear regression (MLR, in particular OLS), and classification methods (mainly k-NN, CART, CP-ANN). The focus of this review is on the main topics of environmental chemistry and ecotoxicology, related to the physico-chemical properties, the reactivity, and biological activity of chemicals of high environmental concern. Thus, the review deals with atmospheric degradation reactions of VOCs by tropospheric oxidants, persistence and long-range transport of POPs, sorption behavior of pesticides (Koc and leaching), bioconcentration, toxicity (acute aquatic toxicity, mutagenicity of PAHs, estrogen binding activity for endocrine disruptors compounds (EDCs)), and finally persistent bioaccumulative and toxic (PBT) behavior for the screening and prioritization of organic pollutants. Common to all the proposed models is the attention paid to model validation for predictive ability (not only internal, but also external for chemicals not participating in the model development) and checking of the chemical domain of applicability. Adherence to such a policy, requested also by the OECD principles, ensures the production of reliable predicted data, useful also in the new European regulation of chemicals, REACH.

Towards interoperable and reproducible QSAR analyses: Exchange of datasets.

PubMed

Spjuth, Ola; Willighagen, Egon L; Guha, Rajarshi; Eklund, Martin; Wikberg, Jarl Es

2010-06-30

QSAR is a widely used method to relate chemical structures to responses or properties based on experimental observations. Much effort has been made to evaluate and validate the statistical modeling in QSAR, but these analyses treat the dataset as fixed. An overlooked but highly important issue is the validation of the setup of the dataset, which comprises addition of chemical structures as well as selection of descriptors and software implementations prior to calculations. This process is hampered by the lack of standards and exchange formats in the field, making it virtually impossible to reproduce and validate analyses and drastically constrain collaborations and re-use of data. We present a step towards standardizing QSAR analyses by defining interoperable and reproducible QSAR datasets, consisting of an open XML format (QSAR-ML) which builds on an open and extensible descriptor ontology. The ontology provides an extensible way of uniquely defining descriptors for use in QSAR experiments, and the exchange format supports multiple versioned implementations of these descriptors. Hence, a dataset described by QSAR-ML makes its setup completely reproducible. We also provide a reference implementation as a set of plugins for Bioclipse which simplifies setup of QSAR datasets, and allows for exporting in QSAR-ML as well as old-fashioned CSV formats. The implementation facilitates addition of new descriptor implementations from locally installed software and remote Web services; the latter is demonstrated with REST and XMPP Web services. Standardized QSAR datasets open up new ways to store, query, and exchange data for subsequent analyses. QSAR-ML supports completely reproducible creation of datasets, solving the problems of defining which software components were used and their versions, and the descriptor ontology eliminates confusions regarding descriptors by defining them crisply. This makes is easy to join, extend, combine datasets and hence work collectively, but also allows for analyzing the effect descriptors have on the statistical model's performance. The presented Bioclipse plugins equip scientists with graphical tools that make QSAR-ML easily accessible for the community.

Towards interoperable and reproducible QSAR analyses: Exchange of datasets

PubMed Central

2010-01-01

Background QSAR is a widely used method to relate chemical structures to responses or properties based on experimental observations. Much effort has been made to evaluate and validate the statistical modeling in QSAR, but these analyses treat the dataset as fixed. An overlooked but highly important issue is the validation of the setup of the dataset, which comprises addition of chemical structures as well as selection of descriptors and software implementations prior to calculations. This process is hampered by the lack of standards and exchange formats in the field, making it virtually impossible to reproduce and validate analyses and drastically constrain collaborations and re-use of data. Results We present a step towards standardizing QSAR analyses by defining interoperable and reproducible QSAR datasets, consisting of an open XML format (QSAR-ML) which builds on an open and extensible descriptor ontology. The ontology provides an extensible way of uniquely defining descriptors for use in QSAR experiments, and the exchange format supports multiple versioned implementations of these descriptors. Hence, a dataset described by QSAR-ML makes its setup completely reproducible. We also provide a reference implementation as a set of plugins for Bioclipse which simplifies setup of QSAR datasets, and allows for exporting in QSAR-ML as well as old-fashioned CSV formats. The implementation facilitates addition of new descriptor implementations from locally installed software and remote Web services; the latter is demonstrated with REST and XMPP Web services. Conclusions Standardized QSAR datasets open up new ways to store, query, and exchange data for subsequent analyses. QSAR-ML supports completely reproducible creation of datasets, solving the problems of defining which software components were used and their versions, and the descriptor ontology eliminates confusions regarding descriptors by defining them crisply. This makes is easy to join, extend, combine datasets and hence work collectively, but also allows for analyzing the effect descriptors have on the statistical model's performance. The presented Bioclipse plugins equip scientists with graphical tools that make QSAR-ML easily accessible for the community. PMID:20591161

Development of structure-activity relationship for metal oxide nanoparticles

NASA Astrophysics Data System (ADS)

Liu, Rong; Zhang, Hai Yuan; Ji, Zhao Xia; Rallo, Robert; Xia, Tian; Chang, Chong Hyun; Nel, Andre; Cohen, Yoram

2013-05-01

Nanomaterial structure-activity relationships (nano-SARs) for metal oxide nanoparticles (NPs) toxicity were investigated using metrics based on dose-response analysis and consensus self-organizing map clustering. The NP cellular toxicity dataset included toxicity profiles consisting of seven different assays for human bronchial epithelial (BEAS-2B) and murine myeloid (RAW 264.7) cells, over a concentration range of 0.39-100 mg L-1 and exposure time up to 24 h, for twenty-four different metal oxide NPs. Various nano-SAR building models were evaluated, based on an initial pool of thirty NP descriptors. The conduction band energy and ionic index (often correlated with the hydration enthalpy) were identified as suitable NP descriptors that are consistent with suggested toxicity mechanisms for metal oxide NPs and metal ions. The best performing nano-SAR with the above two descriptors, built with support vector machine (SVM) model and of validated robustness, had a balanced classification accuracy of ~94%. An applicability domain for the present data was established with a reasonable confidence level of 80%. Given the potential role of nano-SARs in decision making, regarding the environmental impact of NPs, the class probabilities provided by the SVM nano-SAR enabled the construction of decision boundaries with respect to toxicity classification under different acceptance levels of false negative relative to false positive predictions.Nanomaterial structure-activity relationships (nano-SARs) for metal oxide nanoparticles (NPs) toxicity were investigated using metrics based on dose-response analysis and consensus self-organizing map clustering. The NP cellular toxicity dataset included toxicity profiles consisting of seven different assays for human bronchial epithelial (BEAS-2B) and murine myeloid (RAW 264.7) cells, over a concentration range of 0.39-100 mg L-1 and exposure time up to 24 h, for twenty-four different metal oxide NPs. Various nano-SAR building models were evaluated, based on an initial pool of thirty NP descriptors. The conduction band energy and ionic index (often correlated with the hydration enthalpy) were identified as suitable NP descriptors that are consistent with suggested toxicity mechanisms for metal oxide NPs and metal ions. The best performing nano-SAR with the above two descriptors, built with support vector machine (SVM) model and of validated robustness, had a balanced classification accuracy of ~94%. An applicability domain for the present data was established with a reasonable confidence level of 80%. Given the potential role of nano-SARs in decision making, regarding the environmental impact of NPs, the class probabilities provided by the SVM nano-SAR enabled the construction of decision boundaries with respect to toxicity classification under different acceptance levels of false negative relative to false positive predictions. Electronic supplementary information (ESI) available. See DOI: 10.1039/c3nr01533e

Descriptors of Oxygen-Evolution Activity for Oxides: A Statistical Evaluation

DOE PAGES

Hong, Wesley T.; Welsch, Roy E.; Shao-Horn, Yang

2015-12-16

Catalysts for oxygen electrochemical processes are critical for the commercial viability of renewable energy storage and conversion devices such as fuel cells, artificial photosynthesis, and metal-air batteries. Transition metal oxides are an excellent system for developing scalable, non-noble-metal-based catalysts, especially for the oxygen evolution reaction (OER). Central to the rational design of novel catalysts is the development of quantitative structure-activity relation-ships, which correlate the desired catalytic behavior to structural and/or elemental descriptors of materials. The ultimate goal is to use these relationships to guide materials design. In this study, 101 intrinsic OER activities of 51 perovskites were compiled from fivemore » studies in literature and additional measurements made for this work. We explored the behavior and performance of 14 descriptors of the metal-oxygen bond strength using a number of statistical approaches, including factor analysis and linear regression models. We found that these descriptors can be classified into five descriptor families and identify electron occupancy and metal-oxygen covalency as the dominant influences on the OER activity. However, multiple descriptors still need to be considered in order to develop strong predictive relationships, largely outperforming the use of only one or two descriptors (as conventionally done in the field). Here, we confirmed that the number of d electrons, charge-transfer energy (covalency), and optimality of eg occupancy play the important roles, but found that structural factors such as M-O-M bond angle and tolerance factor are relevant as well. With these tools, we demonstrate how statistical learning can be used to draw novel physical insights and combined with data mining to rapidly screen OER electrocatalysts across a wide chemical space.« less

Descriptors of natural thermal regimes in streams and their responsiveness to change in the Pacific Northwest of North America

USGS Publications Warehouse

Arismendi, Ivan; Johnson, Sherri L.; Dunham, Jason B.; Haggerty, Roy

2013-01-01

1. Temperature is a major driver of ecological processes in stream ecosystems, yet the dynamics of thermal regimes remain poorly described. Most work has focused on relatively simple descriptors that fail to capture the full range of conditions that characterise thermal regimes of streams across seasons or throughout the year. 2. To more completely describe thermal regimes, we developed several descriptors of magnitude, variability, frequency, duration and timing of thermal events throughout a year. We evaluated how these descriptors change over time using long-term (1979–2009), continuous temperature data from five relatively undisturbed cold-water streams in western Oregon, U.S.A. In addition to trends for each descriptor, we evaluated similarities among them, as well as patterns of spatial coherence, and temporal synchrony. 3. Using different groups of descriptors, we were able to more fully capture distinct aspects of the full range of variability in thermal regimes across space and time. A subset of descriptors showed both higher coherence and synchrony and, thus, an appropriate level of responsiveness to examine evidence of regional climatic influences on thermal regimes. Most notably, daily minimum values during winter–spring were the most responsive descriptors to potential climatic influences. 4. Overall, thermal regimes in streams we studied showed high frequency and low variability of cold temperatures during the cold-water period in winter and spring, and high frequency and high variability of warm temperatures during the warm-water period in summer and autumn. The cold and warm periods differed in the distribution of events with a higher frequency and longer duration of warm events in summer than cold events in winter. The cold period exhibited lower variability in the duration of events, but showed more variability in timing. 5. In conclusion, our results highlight the importance of a year-round perspective in identifying the most responsive characteristics or descriptors of thermal regimes in streams. The descriptors we provide herein can be applied across hydro-ecological regions to evaluate spatial and temporal patterns in thermal regimes. Evaluation of coherence and synchrony of different components of thermal regimes can facilitate identification of impacts of regional climate variability or local human or natural influences.

High Throughput Heuristics for Prioritizing Human Exposure to ...

EPA Pesticide Factsheets

The risk posed to human health by any of the thousands of untested anthropogenic chemicals in our environment is a function of both the potential hazard presented by the chemical, and the possibility of being exposed. Without the capacity to make quantitative, albeit uncertain, forecasts of exposure, the putative risk of adverse health effect from a chemical cannot be evaluated. We used Bayesian methodology to infer ranges of exposure intakes that are consistent with biomarkers of chemical exposures identified in urine samples from the U.S. population by the National Health and Nutrition Examination Survey (NHANES). We perform linear regression on inferred exposure for demographic subsets of NHANES demarked by age, gender, and weight using high throughput chemical descriptors gleaned from databases and chemical structure-based calculators. We find that five of these descriptors are capable of explaining roughly 50% of the variability across chemicals for all the demographic groups examined, including children aged 6-11. For the thousands of chemicals with no other source of information, this approach allows rapid and efficient prediction of average exposure intake of environmental chemicals. The methods described by this manuscript provide a highly improved methodology for HTS of human exposure to environmental chemicals. The manuscript includes a ranking of 7785 environmental chemicals with respect to potential human exposure, including most of the Tox21 in vit

Shared effects of organic microcontaminants and environmental stressors on biofilms and invertebrates in impaired rivers.

PubMed

Sabater, S; Barceló, D; De Castro-Català, N; Ginebreda, A; Kuzmanovic, M; Petrovic, M; Picó, Y; Ponsatí, L; Tornés, E; Muñoz, I

2016-03-01

Land use type, physical and chemical stressors, and organic microcontaminants were investigated for their effects on the biological communities (biofilms and invertebrates) in several Mediterranean rivers. The diversity of invertebrates, and the scores of the first principal component of a PCA performed with the diatom communities were the best descriptors of the distribution patterns of the biological communities against the river stressors. These two metrics decreased according to the progressive site impairment (associated to higher area of agricultural and urban-industrial, high water conductivity, higher dissolved organic carbon and dissolved inorganic nitrogen concentrations, and higher concentration of organic microcontaminants, particularly pharmaceutical and industrial compounds). The variance partition analyses (RDAs) attributed the major share (10%) of the biological communities' response to the environmental stressors (nutrients, altered discharge, dissolved organic matter), followed by the land use occupation (6%) and of the organic microcontaminants (2%). However, the variance shared by the three groups of descriptors was very high (41%), indicating that their simultaneous occurrence determined most of the variation in the biological communities. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

High-order statistics of weber local descriptors for image representation.

PubMed

Han, Xian-Hua; Chen, Yen-Wei; Xu, Gang

2015-06-01

Highly discriminant visual features play a key role in different image classification applications. This study aims to realize a method for extracting highly-discriminant features from images by exploring a robust local descriptor inspired by Weber's law. The investigated local descriptor is based on the fact that human perception for distinguishing a pattern depends not only on the absolute intensity of the stimulus but also on the relative variance of the stimulus. Therefore, we firstly transform the original stimulus (the images in our study) into a differential excitation-domain according to Weber's law, and then explore a local patch, called micro-Texton, in the transformed domain as Weber local descriptor (WLD). Furthermore, we propose to employ a parametric probability process to model the Weber local descriptors, and extract the higher-order statistics to the model parameters for image representation. The proposed strategy can adaptively characterize the WLD space using generative probability model, and then learn the parameters for better fitting the training space, which would lead to more discriminant representation for images. In order to validate the efficiency of the proposed strategy, we apply three different image classification applications including texture, food images and HEp-2 cell pattern recognition, which validates that our proposed strategy has advantages over the state-of-the-art approaches.

Interactive searching of facial image databases

NASA Astrophysics Data System (ADS)

Nicholls, Robert A.; Shepherd, John W.; Shepherd, Jean

1995-09-01

A set of psychological facial descriptors has been devised to enable computerized searching of criminal photograph albums. The descriptors have been used to encode image databased of up to twelve thousand images. Using a system called FACES, the databases are searched by translating a witness' verbal description into corresponding facial descriptors. Trials of FACES have shown that this coding scheme is more productive and efficient than searching traditional photograph albums. An alternative method of searching the encoded database using a genetic algorithm is currenly being tested. The genetic search method does not require the witness to verbalize a description of the target but merely to indicate a degree of similarity between the target and a limited selection of images from the database. The major drawback of FACES is that is requires a manual encoding of images. Research is being undertaken to automate the process, however, it will require an algorithm which can predict human descriptive values. Alternatives to human derived coding schemes exist using statistical classifications of images. Since databases encoded using statistical classifiers do not have an obvious direct mapping to human derived descriptors, a search method which does not require the entry of human descriptors is required. A genetic search algorithm is being tested for such a purpose.

Revealing cell cycle control by combining model-based detection of periodic expression with novel cis-regulatory descriptors

PubMed Central

Andersson, Claes R; Hvidsten, Torgeir R; Isaksson, Anders; Gustafsson, Mats G; Komorowski, Jan

2007-01-01

Background We address the issue of explaining the presence or absence of phase-specific transcription in budding yeast cultures under different conditions. To this end we use a model-based detector of gene expression periodicity to divide genes into classes depending on their behavior in experiments using different synchronization methods. While computational inference of gene regulatory circuits typically relies on expression similarity (clustering) in order to find classes of potentially co-regulated genes, this method instead takes advantage of known time profile signatures related to the studied process. Results We explain the regulatory mechanisms of the inferred periodic classes with cis-regulatory descriptors that combine upstream sequence motifs with experimentally determined binding of transcription factors. By systematic statistical analysis we show that periodic classes are best explained by combinations of descriptors rather than single descriptors, and that different combinations correspond to periodic expression in different classes. We also find evidence for additive regulation in that the combinations of cis-regulatory descriptors associated with genes periodically expressed in fewer conditions are frequently subsets of combinations associated with genes periodically expression in more conditions. Finally, we demonstrate that our approach retrieves combinations that are more specific towards known cell-cycle related regulators than the frequently used clustering approach. Conclusion The results illustrate how a model-based approach to expression analysis may be particularly well suited to detect biologically relevant mechanisms. Our new approach makes it possible to provide more refined hypotheses about regulatory mechanisms of the cell cycle and it can easily be adjusted to reveal regulation of other, non-periodic, cellular processes. PMID:17939860

Macrophytes, epipelic biofilm, and invertebrates as biotic indicators of physical habitat degradation of lowland streams (Argentina).

PubMed

Cortelezzi, Agustina; Sierra, María Victoria; Gómez, Nora; Marinelli, Claudia; Rodrigues Capítulo, Alberto

2013-07-01

Our objective was to assess the effect of the physical habitat degradation in three lowland streams of Argentina that are subject to different land uses. To address this matter, we looked into some physical habitat alterations, mainly the water quality and channel changes, the impact on macrophytes' community, and the structural and functional descriptors of the epipelic biofilm and invertebrate assemblages. As a consequence of physical and chemical perturbations, we differentiated sampling sites with different degradation levels. The low degraded sites were affected mainly for the suburban land use, the moderately degraded sites for the rural land use, and the highly degraded sites for the urban land use. The data shows that the biotic descriptors that best reflected the environmental degradation were vegetation cover and macrophytes richness, the dominance of tolerant species (epipelic biofilm and invertebrates), algal biomass, O2 consumption by the epipelic biofilm, and invertebrates' richness and diversity. Furthermore, the results obtained highlight the importance of the macrophytes in the lowland streams, where there is a poor diversification of abiotic substrates and where the macrophytes not only provide shelter but also a food source for invertebrates and other trophic levels such as fish. We also noted that both in benthic communities, invertebrates and epipelic biofilm supplied different information: the habitat's physical structure provided by the macrophytes influenced mainly the invertebrate descriptors; meanwhile, the water quality mainly influenced most of the epipelic biofilm descriptors.

Evaluation of marine subareas of Europe using life history parameters and trophic levels of selected fish populations.

PubMed

Jayasinghe, R P Prabath K; Amarasinghe, Upali S; Newton, Alice

2015-12-01

European marine waters include four regional seas that provide valuable ecosystem services to humans, including fish and other seafood. However, these marine environments are threatened by pressures from multiple anthropogenic activities and climate change. The European Marine Strategy Framework Directive (MSFD) was adopted in 2008 to achieve good environmental status (GEnS) in European Seas by year 2020, using an Ecosystem Approach. GEnS is to be assessed using 11 descriptors and up to 56 indicators. In the present analysis two descriptors namely "commercially exploited fish and shellfish populations" and "food webs" were used to evaluate the status of subareas of FAO 27 area. Data on life history parameters, trophic levels and fisheries related data of cod, haddock, saithe, herring, plaice, whiting, hake and sprat were obtained from the FishBase online database and advisory reports of International Council for the Exploration of the Sea (ICES). Subareas inhabited by r and K strategists were identified using interrelationships of life history parameters of commercially important fish stocks. Mean trophic level (MTL) of fish community each subarea was calculated and subareas with species of high and low trophic level were identified. The Fish in Balance (FiB) index was computed for each subarea and recent trends of FiB indices were analysed. The overall environmental status of each subarea was evaluated considering life history trends, MTL and FiB Index. The analysis showed that subareas I, II, V, VIII and IX were assessed as "good" whereas subareas III, IV, VI and VII were assessed as "poor". The subareas assessed as "good" were subject to lower environmental pressures, (less fishing pressure, less eutrophication and more water circulation), while the areas with "poor" environment experienced excessive fishing pressure, eutrophication and disturbed seabed. The evaluation was based on two qualitative descriptors ("commercially exploited fish and shellfish populations" and "food webs") is therefore more robust. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Temporal variability in the importance of hydrologic, biotic, and climatic descriptors of dissolved oxygen dynamics in a shallow tidal-marsh creek

NASA Astrophysics Data System (ADS)

Nelson, N.; Munoz-Carpena, R.; Neale, P.; Tzortziou, M.; Megonigal, P.

2017-12-01

Due to strong abiotic forcing, dissolved oxygen (DO) in shallow tidal creeks often disobeys the conventional explanation of general aquatic DO cycling as biologically-regulated. In the present work, we seek to quantify the relative importance of abiotic (hydrologic and climatic), and biotic (primary productivity as represented by chlorophyll-a) descriptors of tidal creek DO. By fitting multiple linear regression models of DO to hourly chlorophyll-a, water quality, hydrology, and weather data collected in a tidal creek of a Chesapeake Bay marsh (Maryland, USA), temporal shifts (summer - early winter) in the relative importance of tidal creek DO descriptors were uncovered. Moreover, this analysis identified an alternative approach to evaluating tidal stage as a driver of DO by dividing stage into two DO-relevant variables: stage above and below bankfull depth. Within the hydrologic variable class, stage below bankfull depth dominated as an important descriptor, thus highlighting the role of pore water drainage and mixing as influential processes forcing tidal creek DO. Study findings suggest that tidal creek DO dynamics are explained by a balance of hydrologic, climatic, and biotic descriptors during warmer seasons due to many of these variables (i.e., chlorophyll-a, water temperature) acting as tracers of estuarine-marsh water mixing; conversely, in early winter months when estuarine and marsh waters differ less distinctly, hydrologic variables increase in relative importance as descriptors of tidal creek DO. These findings underline important distinctions in the underlying mechanisms dictating DO variability in shallow tidal marsh-creek environments relative to open water estuarine systems.

Temporal variability in the importance of hydrologic, biotic, and climatic descriptors of dissolved oxygen dynamics in a shallow tidal-marsh creek

NASA Astrophysics Data System (ADS)

Nelson, Natalie G.; Muñoz-Carpena, Rafael; Neale, Patrick J.; Tzortziou, Maria; Megonigal, J. Patrick

2017-08-01

Due to strong abiotic forcing, dissolved oxygen (DO) in shallow tidal creeks often disobeys the conventional explanation of general aquatic DO cycling as biologically regulated. In the present work, we seek to quantify the relative importance of abiotic (hydrologic and climatic), and biotic (primary productivity as represented by chlorophyll-a) descriptors of tidal creek DO. By fitting multiple linear regression models of DO to hourly chlorophyll-a, water quality, hydrology, and weather data collected in a tidal creek of a Chesapeake Bay marsh (Maryland, USA), temporal shifts (summer-early winter) in the relative importance of tidal creek DO descriptors were uncovered. Moreover, this analysis identified an alternative approach to evaluating tidal stage as a driver of DO by dividing stage into two DO-relevant variables: stage above and below bankfull depth. Within the hydrologic variable class, stage below bankfull depth dominated as an important descriptor, thus highlighting the role of pore water drainage and mixing as influential processes forcing tidal creek DO. Study findings suggest that tidal creek DO dynamics are explained by a balance of hydrologic, climatic, and biotic descriptors during warmer seasons due to many of these variables (i.e., chlorophyll-a, water temperature) acting as tracers of estuarine-marsh water mixing; conversely, in early winter months when estuarine and marsh waters differ less distinctly, hydrologic variables increase in relative importance as descriptors of tidal creek DO. These findings underline important distinctions in the underlying mechanisms dictating DO variability in shallow tidal marsh-creek environments relative to open water estuarine systems.

TyPol - a new methodology for organic compounds clustering based on their molecular characteristics and environmental behavior.

PubMed

Servien, Rémi; Mamy, Laure; Li, Ziang; Rossard, Virginie; Latrille, Eric; Bessac, Fabienne; Patureau, Dominique; Benoit, Pierre

2014-09-01

Following legislation, the assessment of the environmental risks of 30000-100000 chemical substances is required for their registration dossiers. However, their behavior in the environment and their transfer to environmental components such as water or atmosphere are studied for only a very small proportion of the chemical in laboratory tests or monitoring studies because it is time-consuming and/or cost prohibitive. Therefore, the objective of this work was to develop a new methodology, TyPol, to classify organic compounds, and their degradation products, according to both their behavior in the environment and their molecular properties. The strategy relies on partial least squares analysis and hierarchical clustering. The calculation of molecular descriptors is based on an in silico approach, and the environmental endpoints (i.e. environmental parameters) are extracted from several available databases and literature. The classification of 215 organic compounds inputted in TyPol for this proof-of-concept study showed that the combination of some specific molecular descriptors could be related to a particular behavior in the environment. TyPol also provided an analysis of similarities (or dissimilarities) between organic compounds and their degradation products. Among the 24 degradation products that were inputted, 58% were found in the same cluster as their parents. The robustness of the method was tested and shown to be good. TyPol could help to predict the environmental behavior of a "new" compound (parent compound or degradation product) from its affiliation to one cluster, but also to select representative substances from a large data set in order to answer some specific questions regarding their behavior in the environment. Copyright © 2014 Elsevier Ltd. All rights reserved.

Identification of terms to define unconstrained air transportation demands

NASA Technical Reports Server (NTRS)

Jacobson, I. D.; Kuhilhau, A. R.

1982-01-01

The factors involved in the evaluation of unconstrained air transportation systems were carefully analyzed. By definition an unconstrained system is taken to be one in which the design can employ innovative and advanced concepts no longer limited by present environmental, social, political or regulatory settings. Four principal evaluation criteria are involved: (1) service utilization, based on the operating performance characteristics as viewed by potential patrons; (2) community impacts, reflecting decisions based on the perceived impacts of the system; (3) technological feasibility, estimating what is required to reduce the system to practice; and (4) financial feasibility, predicting the ability of the concepts to attract financial support. For each of these criteria, a set of terms or descriptors was identified, which should be used in the evaluation to render it complete. It is also demonstrated that these descriptors have the following properties: (a) their interpretation may be made by different groups of evaluators; (b) their interpretations and the way they are used may depend on the stage of development of the system in which they are used; (c) in formulating the problem, all descriptors should be addressed independent of the evaluation technique selected.

New molecular descriptors based on local properties at the molecular surface and a boiling-point model derived from them.

PubMed

Ehresmann, Bernd; de Groot, Marcel J; Alex, Alexander; Clark, Timothy

2004-01-01

New molecular descriptors based on statistical descriptions of the local ionization potential, local electron affinity, and the local polarizability at the surface of the molecule are proposed. The significance of these descriptors has been tested by calculating them for the Maybridge database in addition to our set of 26 descriptors reported previously. The new descriptors show little correlation with those already in use. Furthermore, the principal components of the extended set of descriptors for the Maybridge data show that especially the descriptors based on the local electron affinity extend the variance in our set of descriptors, which we have previously shown to be relevant to physical properties. The first nine principal components are shown to be most significant. As an example of the usefulness of the new descriptors, we have set up a QSPR model for boiling points using both the old and new descriptors.

Chaining direct memory access data transfer operations for compute nodes in a parallel computer

DOEpatents

Archer, Charles J.; Blocksome, Michael A.

2010-09-28

Methods, systems, and products are disclosed for chaining DMA data transfer operations for compute nodes in a parallel computer that include: receiving, by an origin DMA engine on an origin node in an origin injection FIFO buffer for the origin DMA engine, a RGET data descriptor specifying a DMA transfer operation data descriptor on the origin node and a second RGET data descriptor on the origin node, the second RGET data descriptor specifying a target RGET data descriptor on the target node, the target RGET data descriptor specifying an additional DMA transfer operation data descriptor on the origin node; creating, by the origin DMA engine, an RGET packet in dependence upon the RGET data descriptor, the RGET packet containing the DMA transfer operation data descriptor and the second RGET data descriptor; and transferring, by the origin DMA engine to a target DMA engine on the target node, the RGET packet.

Replenishing data descriptors in a DMA injection FIFO buffer

DOEpatents

Archer, Charles J [Rochester, MN; Blocksome, Michael A [Rochester, MN; Cernohous, Bob R [Rochester, MN; Heidelberger, Philip [Cortlandt Manor, NY; Kumar, Sameer [White Plains, NY; Parker, Jeffrey J [Rochester, MN

2011-10-11

Methods, apparatus, and products are disclosed for replenishing data descriptors in a Direct Memory Access (`DMA`) injection first-in-first-out (`FIFO`) buffer that include: determining, by a messaging module on an origin compute node, whether a number of data descriptors in a DMA injection FIFO buffer exceeds a predetermined threshold, each data descriptor specifying an application message for transmission to a target compute node; queuing, by the messaging module, a plurality of new data descriptors in a pending descriptor queue if the number of the data descriptors in the DMA injection FIFO buffer exceeds the predetermined threshold; establishing, by the messaging module, interrupt criteria that specify when to replenish the injection FIFO buffer with the plurality of new data descriptors in the pending descriptor queue; and injecting, by the messaging module, the plurality of new data descriptors into the injection FIFO buffer in dependence upon the interrupt criteria.

Environmental Engineering Curricula assessment in the global world

NASA Astrophysics Data System (ADS)

Caporali, Enrica; Catelani, Marcantonio; Manfrida, Giampaolo; Valdiserri, Juna

2014-05-01

Environmental engineers are technicians with specific expertise on the sustainability of human presence in the environment. Among other global dilemmas, to the environmental engineers it is often demanded to be able in developing systematic, innovative solutions in order to simultaneously meet water and energy needs, to build resilience to natural and technological disasters, to more accurately gauge and manage countries' greenhouse gas emissions. The general objectives of the Environmental Engineers are to establish actions of environmental sustainability as well as to verify progress toward global goals or international commitments. The globalization of challenges and problems to be faced, leads, in general, to the globalization of the engineering profession. In particular, since the environmental issues are without boundaries, and many and different are the involved professions and the competences, the environmental engineer must have a multidisciplinary and interdisciplinary approach to adequately answer to the demand of technical innovative knowledge at global scale. The environmental engineers, more and more, are involved in international projects were the effective collaboration requires not only the capacity to communicate in a common technical language, but also the assurance of an adequate and common level of technical competences, knowledge and understanding. The Europe-based EUR ACE system, currently operated by ENAEE - European Network for Accreditation of Engineering Education, can represent the proper framework and accreditation system in order to provide a set of measures to assess the quality of engineering degree programmes in Europe and abroad. In the global frame of the knowledge triangle: education-innovation-research, the accreditation and quality assurance of engineering curricula in Europe is discussed with reference to the Environmental engineering curricula, of the 1st and 2nd cycle, based on the European Credit Transfer System and in accordance with the Bologna Process, offered at School of Engineering, University of Firenze. The application of the accreditation model EUR-ACE to the multidisciplinary first cycle degree in Civil, Building and Environmental Engineering and the more specific second cycle degree in Environmental Engineering is discussed. Particularly, the critical issues to guarantee the quality and the status of environmental engineering graduates, in terms of applying knowledge capacities and technical innovative competences are examined. The expected learning outcomes of the quality assessment according the Dublin descriptors or the more engineering focused EUR-ACE skill descriptors, and at local and global scale are analysed. The system for educating engineers in communicating knowledge and understanding, making informed judgments and choices, capacities to lifelong learning is also assessed. The involvement of the professional working world in the definition of goals in skills, of typical expectations of achievements and abilities, and in general in comparing the teaching profile with the actual needs of the technical workforce, is described. With the aim to promote the innovative aspects related with the environmental engineering education, the important role that science and technology could play is also taken into consideration.

Quantitative structure-retention relationship studies with immobilized artificial membrane chromatography II: partial least squares regression.

PubMed

Li, Jie; Sun, Jin; He, Zhonggui

2007-01-26

We aimed to establish quantitative structure-retention relationship (QSRR) with immobilized artificial membrane (IAM) chromatography using easily understood and obtained physicochemical molecular descriptors and to elucidate which descriptors are critical to affect the interaction process between solutes and immobilized phospholipid membranes. The retention indices (logk(IAM)) of 55 structurally diverse drugs were determined on an immobilized artificial membrane column (IAM.PC.DD2) directly or obtained by extrapolation method for highly hydrophobic compounds. Ten simple physicochemical property descriptors (clogP, rings, rotatory bond, hydro-bond counting, etc.) of these drugs were collected and used to establish QSRR and predict the retention data by partial least squares regression (PLSR). Five descriptors, clogP, rotatory bond (RotB), rings, molecular weight (MW) and total surface area (TSA), were reserved by using the Variable Importance for Projection (VIP) values as criterion to build the final PLSR model. An external test set was employed to verify the QSRR based on the training set with the five variables, and QSRR by PLSR exhibited a satisfying predictive ability with R(p)=0.902 and RMSE(p)=0.400. Comparison of coefficients of centered and scaled variables by PLSR demonstrated that, for the descriptors studied, clogP and TSA have the most significant positive effect but the rotatable bond has significant negative effect on drug IAM chromatographic retention.

Novel texture-based descriptors for tool wear condition monitoring

NASA Astrophysics Data System (ADS)

Antić, Aco; Popović, Branislav; Krstanović, Lidija; Obradović, Ratko; Milošević, Mijodrag

2018-01-01

All state-of-the-art tool condition monitoring systems (TCM) in the tool wear recognition task, especially those that use vibration sensors, heavily depend on the choice of descriptors containing information about the tool wear state which are extracted from the particular sensor signals. All other post-processing techniques do not manage to increase the recognition precision if those descriptors are not discriminative enough. In this work, we propose a tool wear monitoring strategy which relies on the novel texture based descriptors. We consider the module of the Short Term Discrete Fourier Transform (STDFT) spectra obtained from the particular vibration sensors signal utterance as the 2D textured image. This is done by identifying the time scale of STDFT as the first dimension, and the frequency scale as the second dimension of the particular textured image. The obtained textured image is then divided into particular 2D texture patches, covering a part of the frequency range of interest. After applying the appropriate filter bank, 2D textons are extracted for each predefined frequency band. By averaging in time, we extract from the textons for each band of interest the information regarding the Probability Density Function (PDF) in the form of lower order moments, thus obtaining robust tool wear state descriptors. We validate the proposed features by the experiments conducted on the real TCM system, obtaining the high recognition accuracy.

Genomic signal processing methods for computation of alignment-free distances from DNA sequences.

PubMed

Borrayo, Ernesto; Mendizabal-Ruiz, E Gerardo; Vélez-Pérez, Hugo; Romo-Vázquez, Rebeca; Mendizabal, Adriana P; Morales, J Alejandro

2014-01-01

Genomic signal processing (GSP) refers to the use of digital signal processing (DSP) tools for analyzing genomic data such as DNA sequences. A possible application of GSP that has not been fully explored is the computation of the distance between a pair of sequences. In this work we present GAFD, a novel GSP alignment-free distance computation method. We introduce a DNA sequence-to-signal mapping function based on the employment of doublet values, which increases the number of possible amplitude values for the generated signal. Additionally, we explore the use of three DSP distance metrics as descriptors for categorizing DNA signal fragments. Our results indicate the feasibility of employing GAFD for computing sequence distances and the use of descriptors for characterizing DNA fragments.

Genomic Signal Processing Methods for Computation of Alignment-Free Distances from DNA Sequences

PubMed Central

Borrayo, Ernesto; Mendizabal-Ruiz, E. Gerardo; Vélez-Pérez, Hugo; Romo-Vázquez, Rebeca; Mendizabal, Adriana P.; Morales, J. Alejandro

2014-01-01

Genomic signal processing (GSP) refers to the use of digital signal processing (DSP) tools for analyzing genomic data such as DNA sequences. A possible application of GSP that has not been fully explored is the computation of the distance between a pair of sequences. In this work we present GAFD, a novel GSP alignment-free distance computation method. We introduce a DNA sequence-to-signal mapping function based on the employment of doublet values, which increases the number of possible amplitude values for the generated signal. Additionally, we explore the use of three DSP distance metrics as descriptors for categorizing DNA signal fragments. Our results indicate the feasibility of employing GAFD for computing sequence distances and the use of descriptors for characterizing DNA fragments. PMID:25393409

Exploration of the Medicinal Peptide Space.

PubMed

Gevaert, Bert; Stalmans, Sofie; Wynendaele, Evelien; Taevernier, Lien; Bracke, Nathalie; D'Hondt, Matthias; De Spiegeleer, Bart

2016-01-01

The chemical properties of peptide medicines, known as the 'medicinal peptide space' is considered a multi-dimensional subset of the global peptide space, where each dimension represents a chemical descriptor. These descriptors can be linked to biofunctional, medicinal properties to varying degrees. Knowledge of this space can increase the efficiency of the peptide-drug discovery and development process, as well as advance our understanding and classification of peptide medicines. For 245 peptide drugs, already available on the market or in clinical development, multivariate dataexploration was performed using peptide relevant physicochemical descriptors, their specific peptidedrug target and their clinical use. Our retrospective analysis indicates that clusters in the medicinal peptide space are located in a relatively narrow range of the physicochemical space: dense and empty regions were found, which can be explored for the discovery of novel peptide drugs.

Hierarchical Event Descriptors (HED): Semi-Structured Tagging for Real-World Events in Large-Scale EEG

PubMed Central

Bigdely-Shamlo, Nima; Cockfield, Jeremy; Makeig, Scott; Rognon, Thomas; La Valle, Chris; Miyakoshi, Makoto; Robbins, Kay A.

2016-01-01

Real-world brain imaging by EEG requires accurate annotation of complex subject-environment interactions in event-rich tasks and paradigms. This paper describes the evolution of the Hierarchical Event Descriptor (HED) system for systematically describing both laboratory and real-world events. HED version 2, first described here, provides the semantic capability of describing a variety of subject and environmental states. HED descriptions can include stimulus presentation events on screen or in virtual worlds, experimental or spontaneous events occurring in the real world environment, and events experienced via one or multiple sensory modalities. Furthermore, HED 2 can distinguish between the mere presence of an object and its actual (or putative) perception by a subject. Although the HED framework has implicit ontological and linked data representations, the user-interface for HED annotation is more intuitive than traditional ontological annotation. We believe that hiding the formal representations allows for a more user-friendly interface, making consistent, detailed tagging of experimental, and real-world events possible for research users. HED is extensible while retaining the advantages of having an enforced common core vocabulary. We have developed a collection of tools to support HED tag assignment and validation; these are available at hedtags.org. A plug-in for EEGLAB (sccn.ucsd.edu/eeglab), CTAGGER, is also available to speed the process of tagging existing studies. PMID:27799907

Stochastic Analysis and Design of Heterogeneous Microstructural Materials System

NASA Astrophysics Data System (ADS)

Xu, Hongyi

Advanced materials system refers to new materials that are comprised of multiple traditional constituents but complex microstructure morphologies, which lead to superior properties over the conventional materials. To accelerate the development of new advanced materials system, the objective of this dissertation is to develop a computational design framework and the associated techniques for design automation of microstructure materials systems, with an emphasis on addressing the uncertainties associated with the heterogeneity of microstructural materials. Five key research tasks are identified: design representation, design evaluation, design synthesis, material informatics and uncertainty quantification. Design representation of microstructure includes statistical characterization and stochastic reconstruction. This dissertation develops a new descriptor-based methodology, which characterizes 2D microstructures using descriptors of composition, dispersion and geometry. Statistics of 3D descriptors are predicted based on 2D information to enable 2D-to-3D reconstruction. An efficient sequential reconstruction algorithm is developed to reconstruct statistically equivalent random 3D digital microstructures. In design evaluation, a stochastic decomposition and reassembly strategy is developed to deal with the high computational costs and uncertainties induced by material heterogeneity. The properties of Representative Volume Elements (RVE) are predicted by stochastically reassembling SVE elements with stochastic properties into a coarse representation of the RVE. In design synthesis, a new descriptor-based design framework is developed, which integrates computational methods of microstructure characterization and reconstruction, sensitivity analysis, Design of Experiments (DOE), metamodeling and optimization the enable parametric optimization of the microstructure for achieving the desired material properties. Material informatics is studied to efficiently reduce the dimension of microstructure design space. This dissertation develops a machine learning-based methodology to identify the key microstructure descriptors that highly impact properties of interest. In uncertainty quantification, a comparative study on data-driven random process models is conducted to provide guidance for choosing the most accurate model in statistical uncertainty quantification. Two new goodness-of-fit metrics are developed to provide quantitative measurements of random process models' accuracy. The benefits of the proposed methods are demonstrated by the example of designing the microstructure of polymer nanocomposites. This dissertation provides material-generic, intelligent modeling/design methodologies and techniques to accelerate the process of analyzing and designing new microstructural materials system.

Considering ionic state in modeling sorption of pharmaceuticals to sewage sludge.

PubMed

Rybacka, Aleksandra; Andersson, Patrik L

2016-12-01

Information on the partitioning of chemicals between particulate matter and water in sewage treatment plants (STPs) can be used to predict their subsequent environmental fate. However, this information can be challenging to acquire, especially for pharmaceuticals that are frequently present in ionized forms. This study investigated the relationship between the ionization state of active pharmaceutical ingredients (APIs) and their partitioning between water and sludge in STPs. We also investigated the underlying mechanisms of sludge sorption by using chemical descriptors based on ionized structures, and evaluated the usefulness of these descriptors in quantitative structure-property relationship (QSPR) modeling. K D values were collected for 110 APIs, which were classified as neutral, positive, or negative at pH 7. The models with the highest performance had the R 2 Y and Q 2 values of above 0.75 and 0.65, respectively. We found that the dominant intermolecular forces governing the interactions of neutral and positively charged APIs with sludge are hydrophobic, pi-pi, and dipole-dipole interactions, whereas the interactions of negatively charged APIs with sludge were mainly governed by covalent bonding as well as ion-ion, ion-dipole, and dipole-dipole interactions; hydrophobicity-driven interactions were rather unimportant. Including charge-related descriptors improved the models' performance by 5-10%, underlining the importance of electrostatic interactions. The use of descriptors calculated for ionized structures did not improve the model statistics for positive and negative APIs, but slightly increased model performance for neutral APIs. We attribute this to a better description of neutral zwitterions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Synthesizing Equivalence Indices for the Comparative Evaluation of Technoeconomic Efficiency of Industrial Processes at the Design/Re-engineering Level

NASA Astrophysics Data System (ADS)

Fotilas, P.; Batzias, A. F.

2007-12-01

The equivalence indices synthesized for the comparative evaluation of technoeconomic efficiency of industrial processes are of critical importance since they serve as both, (i) positive/analytic descriptors of the physicochemical nature of the process and (ii) measures of effectiveness, especially helpful for investigated competitiveness in the industrial/energy/environmental sector of the economy. In the present work, a new algorithmic procedure has been developed, which initially standardizes a real industrial process, then analyzes it as a compromise of two ideal processes, and finally synthesizes the index that can represent/reconstruct the real process as a result of the trade-off between the two ideal processes taking as parental prototypes. The same procedure makes fuzzy multicriteria ranking within a set of pre-selected industrial processes for two reasons: (a) to analyze the process most representative of the production/treatment under consideration, (b) to use the `second best' alternative as a dialectic pole in absence of the two ideal processes mentioned above. An implantation of this procedure is presented, concerning a facility of biological wastewater treatment with six alternatives: activated sludge through (i) continuous-flow incompletely-stirred tank reactors in series, (ii) a plug flow reactor with dispersion, (iii) an oxidation ditch, and biological processing through (iv) a trickling filter, (v) rotating contactors, (vi) shallow ponds. The criteria used for fuzzy (to count for uncertainty) ranking are capital cost, operating cost, environmental friendliness, reliability, flexibility, extendibility. Two complementary indices were synthesized for the (ii)-alternative ranked first and their quantitative expressions were derived, covering a variety of kinetic models as well as recycle/bypass conditions. Finally, analysis of estimating the optimal values of these indices at maximum technoeconomic efficiency is presented and the implications (expected to be) caused by exogenous and endogenous factors (e.g., environmental standards change and innovative energy savings/substitution, respectively) are discussed by means of marginal efficiency graphs.

The EVER-EST portal as support for the Sea Monitoring Virtual Research Community, through the sharing of resources, enabling dynamic collaboration and promoting community engagement

NASA Astrophysics Data System (ADS)

Foglini, Federica; Grande, Valentina; De Leo, Francesco; Mantovani, Simone; Ferraresi, Sergio

2017-04-01

EVER-EST offers a framework based on advanced services delivered both at the e-infrastructure and domain-specific level, with the objective of supporting each phase of the Earth Science Research and Information Lifecycle. It provides innovative e-research services to Earth Science user communities for communication, cross-validation and the sharing of knowledge and science outputs. The project follows a user-centric approach: real use cases taken from pre-selected Virtual Research Communities (VRC) covering different Earth Science research scenarios drive the implementation of the Virtual Research Environment (VRE) services and capabilities. The Sea Monitoring community is involved in the evaluation of the EVER-EST infrastructure. The community of potential users is wide and heterogeneous including both multi-disciplinary scientists and national/international agencies and authorities (e.g. MPAs directors, technicians from regional agencies like ARPA in Italy, the technicians working for the Ministry of the Environment) dealing with the adoption of a better way of measuring the quality of the environment. The scientific community has the main role of assessing the best criteria and indicators for defining the Good Environmental Status (GES) in their own sub regions, and implementing methods, protocols and tools for monitoring the GES descriptors. According to the Marine Strategy Framework Directive (MSFD), the environmental status of marine waters is defined by 11 descriptors, and forms a proposed set of 29 associated criteria and 56 different indicators. The objective of the Sea Monitoring VRC is to provide useful and applicable contributions to the evaluation of the descriptors: D1.Biodiversity, D2.Non-indigenous species and D6.Seafloor Integrity (http://ec.europa.eu/environment/marine/good-environmental-status/index_en.htm). The main challenges for the community members are: 1. discovery of existing data and products distributed among different infrastructures; 2. sharing methodologies about the GES evaluation and monitoring; 3. working on the same workflows and data; 4. adopting shared powerful tools for data processing (e.g. software and servers). The Sea Monitoring portal provides the VRC users with tools and services aimed at enhancing their ability to interoperate and share knowledge, experience and methods for GES assessment and monitoring, such as: •digital information services for data management, exploitation and preservation (accessibility of heterogeneous data sources including associated documentation); •e-collaboration services to communicate and share knowledge, ideas, protocols and workflows; •e-learning services to facilitate the use of common workflows for assessing GES indicators; •e-research services for workflow management, validation and verification, as well as visualization and interactive services. The current study is co-financed by the European Union's Horizon 2020 research and innovation programme under the EVER-EST project (Grant Agreement No. 674907).

Developing a CD-CBM Anticipatory Approach for Cavitation - Defining a Model Descriptor Consistent Between Processes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Allgood, G.O.; Dress, W.B.; Kercel, S.W.

1999-05-10

A major problem with cavitation in pumps and other hydraulic devices is that there is no effective method for detecting or predicting its inception. The traditional approach is to declare the pump in cavitation when the total head pressure drops by some arbitrary value (typically 3o/0) in response to a reduction in pump inlet pressure. However, the pump is already cavitating at this point. A method is needed in which cavitation events are captured as they occur and characterized by their process dynamics. The object of this research was to identify specific features of cavitation that could be used asmore » a model-based descriptor in a context-dependent condition-based maintenance (CD-CBM) anticipatory prognostic and health assessment model. This descriptor was based on the physics of the phenomena, capturing the salient features of the process dynamics. An important element of this concept is the development and formulation of the extended process feature vector @) or model vector. Thk model-based descriptor encodes the specific information that describes the phenomena and its dynamics and is formulated as a data structure consisting of several elements. The first is a descriptive model abstracting the phenomena. The second is the parameter list associated with the functional model. The third is a figure of merit, a single number between [0,1] representing a confidence factor that the functional model and parameter list actually describes the observed data. Using this as a basis and applying it to the cavitation problem, any given location in a flow loop will have this data structure, differing in value but not content. The extended process feature vector is formulated as follows: E`> [ , {parameter Iist}, confidence factor]. (1) For this study, the model that characterized cavitation was a chirped-exponentially decaying sinusoid. Using the parameters defined by this model, the parameter list included frequency, decay, and chirp rate. Based on this, the process feature vector has the form: @=> [, {01 = a, ~= b, ~ = c}, cf = 0.80]. (2) In this experiment a reversible catastrophe was examined. The reason for this is that the same catastrophe could be repeated to ensure the statistical significance of the data.« less

Geopressured geothermal bibliography. Volume I. Citation extracts. Second edition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sepehrnoori, K.; Carter, F.; Schneider, R.

This annoted bibliography contains 1131 citations. It represents reports, papers, and articles appearing over the past eighteen years covering topics from the scientific and technical aspects of geopressured geothermal reservoirs to the social, environmental, and legal considerations of exploiting those reservoirs for their energy resources. Six indexes include: author, conference title, descriptor, journal title, report number, and sponsor. (MHR)

Southern Ocean Echinoids database – An updated version of Antarctic, Sub-Antarctic and cold temperate echinoid database

PubMed Central

Fabri-Ruiz, Salomé; Saucède, Thomas; Danis, Bruno; David, Bruno

2017-01-01

Abstract This database includes over 7,100 georeferenced occurrence records of sea urchins (Echinodermata: Echinoidea) obtained from samples collected in the Southern Ocean (+180°W/+180°E; -35°/-78°S) during oceanographic cruises led over 150 years, from 1872 to 2015. Echinoids are common organisms of Southern Ocean benthic communities. A total of 201 species is recorded, which display contrasting depth ranges and distribution patterns across austral provinces and bioregions. Echinoid species show various ecological traits including different nutrition and reproductive strategies. Information on taxonomy, sampling sites, and sampling sources are also made available. Environmental descriptors that are relevant to echinoid ecology are also made available for the study area (-180°W/+180°E; -45°/-78°S) and for the following decades: 1955–1964, 1965–1974, 1975–1984, 1985–1994 and 1995–2012. They were compiled from different sources and transformed to the same grid cell resolution of 0.1° per pixel. We also provide future projections for environmental descriptors established based on the Bio-Oracle database (Tyberghein et al. 2012). PMID:29134013

Modifications of the chemical structure of phenolics differentially affect physiological activities in pulvinar cells of Mimosa pudica L. II. Influence of various molecular properties in relation to membrane transport.

PubMed

Rocher, Françoise; Roblin, Gabriel; Chollet, Jean-François

2017-03-01

Early prediction of compound absorption by cells is of considerable importance in the building of an integrated scheme describing the impact of a compound on intracellular biological processes. In this scope, we study the structure-activity relationships of several benzoic acid-related phenolics which are involved in many plant biological phenomena (growth, flowering, allelopathy, defense processes). Using the partial least squares (PLS) regression method, the impact of molecular descriptors that have been shown to play an important role concerning the uptake of pharmacologically active compounds by animal cells was analyzed in terms of the modification of membrane potential, variations in proton flux, and inhibition of the osmocontractile reaction of pulvinar cells of Mimosa pudica leaves. The hydrogen bond donors (HBD) and hydrogen bond acceptors (HBA), polar surface area (PSA), halogen ratio (Hal ratio), number of rotatable bonds (FRB), molar volume (MV), molecular weight (MW), and molar refractivity (MR) were considered in addition to two physicochemical properties (logD and the amount of non-dissociated form in relation to pKa). HBD + HBA and PSA predominantly impacted the three biological processes compared to the other descriptors. The coefficient of determination in the quantitative structure-activity relationship (QSAR) models indicated that a major part of the observed seismonasty inhibition and proton flux modification can be explained by the impact of these descriptors, whereas this was not the case for membrane potential variations. These results indicate that the transmembrane transport of the compounds is a predominant component. An increasing number of implicated descriptors as the biological processes become more complex may reflect their impacts on an increasing number of sites in the cell. The determination of the most efficient effectors may lead to a practical use to improve drugs in the control of microbial attacks on plants.

Descriptor selection for banana accessions based on univariate and multivariate analysis.

PubMed

Brandão, L P; Souza, C P F; Pereira, V M; Silva, S O; Santos-Serejo, J A; Ledo, C A S; Amorim, E P

2013-05-14

Our objective was to establish a minimum number of morphological descriptors for the characterization of banana germplasm and evaluate the efficiency of removal of redundant characters, based on univariate and multivariate statistical analyses. Phenotypic characterization was made of 77 accessions from Bahia, Brazil, using 92 descriptors. The selection of the descriptors was carried out by principal components analysis (quantitative) and by entropy (multi-category). Efficiency of elimination was analyzed by a comparative study between the clusters formed, taking into consideration all 92 descriptors and smaller groups. The selected descriptors were analyzed with the Ward-MLM procedure and a combined matrix formed by the Gower algorithm. We were able to reduce the number of descriptors used for characterizing the banana germplasm (42%). The correlation between the matrices considering the 92 descriptors and the selected ones was 0.82, showing that the reduction in the number of descriptors did not influence estimation of genetic variability between the banana accessions. We conclude that removing these descriptors caused no loss of information, considering the groups formed from pre-established criteria, including subgroup/subspecies.

Human action recognition based on point context tensor shape descriptor

NASA Astrophysics Data System (ADS)

Li, Jianjun; Mao, Xia; Chen, Lijiang; Wang, Lan

2017-07-01

Motion trajectory recognition is one of the most important means to determine the identity of a moving object. A compact and discriminative feature representation method can improve the trajectory recognition accuracy. This paper presents an efficient framework for action recognition using a three-dimensional skeleton kinematic joint model. First, we put forward a rotation-scale-translation-invariant shape descriptor based on point context (PC) and the normal vector of hypersurface to jointly characterize local motion and shape information. Meanwhile, an algorithm for extracting the key trajectory based on the confidence coefficient is proposed to reduce the randomness and computational complexity. Second, to decrease the eigenvalue decomposition time complexity, a tensor shape descriptor (TSD) based on PC that can globally capture the spatial layout and temporal order to preserve the spatial information of each frame is proposed. Then, a multilinear projection process is achieved by tensor dynamic time warping to map the TSD to a low-dimensional tensor subspace of the same size. Experimental results show that the proposed shape descriptor is effective and feasible, and the proposed approach obtains considerable performance improvement over the state-of-the-art approaches with respect to accuracy on a public action dataset.

Log-Gabor Weber descriptor for face recognition

NASA Astrophysics Data System (ADS)

Li, Jing; Sang, Nong; Gao, Changxin

2015-09-01

The Log-Gabor transform, which is suitable for analyzing gradually changing data such as in iris and face images, has been widely used in image processing, pattern recognition, and computer vision. In most cases, only the magnitude or phase information of the Log-Gabor transform is considered. However, the complementary effect taken by combining magnitude and phase information simultaneously for an image-feature extraction problem has not been systematically explored in the existing works. We propose a local image descriptor for face recognition, called Log-Gabor Weber descriptor (LGWD). The novelty of our LGWD is twofold: (1) to fully utilize the information from the magnitude or phase feature of multiscale and orientation Log-Gabor transform, we apply the Weber local binary pattern operator to each transform response. (2) The encoded Log-Gabor magnitude and phase information are fused at the feature level by utilizing kernel canonical correlation analysis strategy, considering that feature level information fusion is effective when the modalities are correlated. Experimental results on the AR, Extended Yale B, and UMIST face databases, compared with those available from recent experiments reported in the literature, show that our descriptor yields a better performance than state-of-the art methods.

Informing the Human Plasma Protein Binding of Environmental Chemicals by Machine Learning in the Pharmaceutical Space: Applicability Domain and Limits of Predictability.

PubMed

Ingle, Brandall L; Veber, Brandon C; Nichols, John W; Tornero-Velez, Rogelio

2016-11-28

The free fraction of a xenobiotic in plasma (F ub ) is an important determinant of chemical adsorption, distribution, metabolism, elimination, and toxicity, yet experimental plasma protein binding data are scarce for environmentally relevant chemicals. The presented work explores the merit of utilizing available pharmaceutical data to predict F ub for environmentally relevant chemicals via machine learning techniques. Quantitative structure-activity relationship (QSAR) models were constructed with k nearest neighbors (kNN), support vector machines (SVM), and random forest (RF) machine learning algorithms from a training set of 1045 pharmaceuticals. The models were then evaluated with independent test sets of pharmaceuticals (200 compounds) and environmentally relevant ToxCast chemicals (406 total, in two groups of 238 and 168 compounds). The selection of a minimal feature set of 10-15 2D molecular descriptors allowed for both informative feature interpretation and practical applicability domain assessment via a bounded box of descriptor ranges and principal component analysis. The diverse pharmaceutical and environmental chemical sets exhibit similarities in terms of chemical space (99-82% overlap), as well as comparable bias and variance in constructed learning curves. All the models exhibit significant predictability with mean absolute errors (MAE) in the range of 0.10-0.18F ub . The models performed best for highly bound chemicals (MAE 0.07-0.12), neutrals (MAE 0.11-0.14), and acids (MAE 0.14-0.17). A consensus model had the highest accuracy across both pharmaceuticals (MAE 0.151-0.155) and environmentally relevant chemicals (MAE 0.110-0.131). The inclusion of the majority of the ToxCast test sets within the AD of the consensus model, coupled with high prediction accuracy for these chemicals, indicates the model provides a QSAR for F ub that is broadly applicable to both pharmaceuticals and environmentally relevant chemicals.

Prediction of drug transport processes using simple parameters and PLS statistics. The use of ACD/logP and ACD/ChemSketch descriptors.

PubMed

Osterberg, T; Norinder, U

2001-01-01

A method of modelling and predicting biopharmaceutical properties using simple theoretically computed molecular descriptors and multivariate statistics has been investigated for several data sets related to solubility, IAM chromatography, permeability across Caco-2 cell monolayers, human intestinal perfusion, brain-blood partitioning, and P-glycoprotein ATPase activity. The molecular descriptors (e.g. molar refractivity, molar volume, index of refraction, surface tension and density) and logP were computed with ACD/ChemSketch and ACD/logP, respectively. Good statistical models were derived that permit simple computational prediction of biopharmaceutical properties. All final models derived had R(2) values ranging from 0.73 to 0.95 and Q(2) values ranging from 0.69 to 0.86. The RMSEP values for the external test sets ranged from 0.24 to 0.85 (log scale).

An object-based approach to weather analysis and its applications

NASA Astrophysics Data System (ADS)

Troemel, Silke; Diederich, Malte; Horvath, Akos; Simmer, Clemens; Kumjian, Matthew

2013-04-01

The research group 'Object-based Analysis and SEamless prediction' (OASE) within the Hans Ertel Centre for Weather Research programme (HErZ) pursues an object-based approach to weather analysis. The object-based tracking approach adopts the Lagrange perspective by identifying and following the development of convective events over the course of their lifetime. Prerequisites of the object-based analysis are a high-resolved observational data base and a tracking algorithm. A near real-time radar and satellite remote sensing-driven 3D observation-microphysics composite covering Germany, currently under development, contains gridded observations and estimated microphysical quantities. A 3D scale-space tracking identifies convective rain events in the dual-composite and monitors the development over the course of their lifetime. The OASE-group exploits the object-based approach in several fields of application: (1) For a better understanding and analysis of precipitation processes responsible for extreme weather events, (2) in nowcasting, (3) as a novel approach for validation of meso-γ atmospheric models, and (4) in data assimilation. Results from the different fields of application will be presented. The basic idea of the object-based approach is to identify a small set of radar- and satellite derived descriptors which characterize the temporal development of precipitation systems which constitute the objects. So-called proxies of the precipitation process are e.g. the temporal change of the brightband, vertically extensive columns of enhanced differential reflectivity ZDR or the cloud top temperature and heights identified in the 4D field of ground-based radar reflectivities and satellite retrievals generated by a cell during its life time. They quantify (micro-) physical differences among rain events and relate to the precipitation yield. Analyses on the informative content of ZDR columns as precursor for storm evolution for example will be presented to demonstrate the use of such system-oriented predictors for nowcasting. Columns of differential reflectivity ZDR measured by polarimetric weather radars are prominent signatures associated with thunderstorm updrafts. Since greater vertical velocities can loft larger drops and water-coated ice particles to higher altitudes above the environmental freezing level, the integrated ZDR column above the freezing level increases with increasing updraft intensity. Validation of atmospheric models concerning precipitation representation or prediction is usually confined to comparisons of precipitation fields or their temporal and spatial statistics. A comparison of the rain rates alone, however, does not immediately explain discrepancies between models and observations, because similar rain rates might be produced by different processes. Within the event-based approach for validation of models both observed and modeled rain events are analyzed by means of proxies of the precipitation process. Both sets of descriptors represent the basis for model validation since different leading descriptors - in a statistical sense- hint at process formulations potentially responsible for model failures.

How diverse are diversity assessment methods? A comparative analysis and benchmarking of molecular descriptor space.

PubMed

Koutsoukas, Alexios; Paricharak, Shardul; Galloway, Warren R J D; Spring, David R; Ijzerman, Adriaan P; Glen, Robert C; Marcus, David; Bender, Andreas

2014-01-27

Chemical diversity is a widely applied approach to select structurally diverse subsets of molecules, often with the objective of maximizing the number of hits in biological screening. While many methods exist in the area, few systematic comparisons using current descriptors in particular with the objective of assessing diversity in bioactivity space have been published, and this shortage is what the current study is aiming to address. In this work, 13 widely used molecular descriptors were compared, including fingerprint-based descriptors (ECFP4, FCFP4, MACCS keys), pharmacophore-based descriptors (TAT, TAD, TGT, TGD, GpiDAPH3), shape-based descriptors (rapid overlay of chemical structures (ROCS) and principal moments of inertia (PMI)), a connectivity-matrix-based descriptor (BCUT), physicochemical-property-based descriptors (prop2D), and a more recently introduced molecular descriptor type (namely, "Bayes Affinity Fingerprints"). We assessed both the similar behavior of the descriptors in assessing the diversity of chemical libraries, and their ability to select compounds from libraries that are diverse in bioactivity space, which is a property of much practical relevance in screening library design. This is particularly evident, given that many future targets to be screened are not known in advance, but that the library should still maximize the likelihood of containing bioactive matter also for future screening campaigns. Overall, our results showed that descriptors based on atom topology (i.e., fingerprint-based descriptors and pharmacophore-based descriptors) correlate well in rank-ordering compounds, both within and between descriptor types. On the other hand, shape-based descriptors such as ROCS and PMI showed weak correlation with the other descriptors utilized in this study, demonstrating significantly different behavior. We then applied eight of the molecular descriptors compared in this study to sample a diverse subset of sample compounds (4%) from an initial population of 2587 compounds, covering the 25 largest human activity classes from ChEMBL and measured the coverage of activity classes by the subsets. Here, it was found that "Bayes Affinity Fingerprints" achieved an average coverage of 92% of activity classes. Using the descriptors ECFP4, GpiDAPH3, TGT, and random sampling, 91%, 84%, 84%, and 84% of the activity classes were represented in the selected compounds respectively, followed by BCUT, prop2D, MACCS, and PMI (in order of decreasing performance). In addition, we were able to show that there is no visible correlation between compound diversity in PMI space and in bioactivity space, despite frequent utilization of PMI plots to this end. To summarize, in this work, we assessed which descriptors select compounds with high coverage of bioactivity space, and can hence be used for diverse compound selection for biological screening. In cases where multiple descriptors are to be used for diversity selection, this work describes which descriptors behave complementarily, and can hence be used jointly to focus on different aspects of diversity in chemical space.

A Global Covariance Descriptor for Nuclear Atypia Scoring in Breast Histopathology Images.

PubMed

Khan, Adnan Mujahid; Sirinukunwattana, Korsuk; Rajpoot, Nasir

2015-09-01

Nuclear atypia scoring is a diagnostic measure commonly used to assess tumor grade of various cancers, including breast cancer. It provides a quantitative measure of deviation in visual appearance of cell nuclei from those in normal epithelial cells. In this paper, we present a novel image-level descriptor for nuclear atypia scoring in breast cancer histopathology images. The method is based on the region covariance descriptor that has recently become a popular method in various computer vision applications. The descriptor in its original form is not suitable for classification of histopathology images as cancerous histopathology images tend to possess diversely heterogeneous regions in a single field of view. Our proposed image-level descriptor, which we term as the geodesic mean of region covariance descriptors, possesses all the attractive properties of covariance descriptors lending itself to tractable geodesic-distance-based k-nearest neighbor classification using efficient kernels. The experimental results suggest that the proposed image descriptor yields high classification accuracy compared to a variety of widely used image-level descriptors.

TEXTINFO: a tool for automatic determination of patient clinical profiles using text analysis.

PubMed Central

Borst, F.; Lyman, M.; Nhàn, N. T.; Tick, L. J.; Sager, N.; Scherrer, J. R.

1991-01-01

The clinical data contained in narrative patient documents is made available via grammatical and semantic processing. Retrievals from the resulting relational database tables are matched against a set of clinical descriptors to obtain clinical profiles of the patients in terms of the descriptors present in the documents. Discharge summaries of 57 Dept. of Digestive Surgery patients were processed in this manner. Factor analysis and discriminant analysis procedures were then applied, showing the profiles to be useful for diagnosis definitions (by establishing relations between diagnoses and clinical findings), for diagnosis assessment (by viewing the match between a definition and observed events recorded in a patient text), and potentially for outcome evaluation based on the classification abilities of clinical signs. PMID:1807679

Predicting hepatotoxicity using ToxCast in vitro bioactivity and ...

EPA Pesticide Factsheets

Background: The U.S. EPA ToxCastTM program is screening thousands of environmental chemicals for bioactivity using hundreds of high-throughput in vitro assays to build predictive models of toxicity. We represented chemicals based on bioactivity and chemical structure descriptors then used supervised machine learning to predict their hepatotoxic effects.Results: A set of 677 chemicals were represented by 711 in vitro bioactivity descriptors (from ToxCast assays), 4,376 chemical structure descriptors (from QikProp, OpenBabel, PADEL, and PubChem), and three hepatotoxicity categories (from animal studies). Hepatotoxicants were defined by rat liver histopathology observed after chronic chemical testing and grouped into hypertrophy (161), injury (101) and proliferative lesions (99). Classifiers were built using six machine learning algorithms: linear discriminant analysis (LDA), Naïve Bayes (NB), support vector classification (SVM), classification and regression trees (CART), k-nearest neighbors (KNN) and an ensemble of classifiers (ENSMB). Classifiers of hepatotoxicity were built using chemical structure, ToxCast bioactivity, and a hybrid representation. Predictive performance was evaluated using 10-fold cross-validation testing and in-loop, filter-based, feature subset selection. Hybrid classifiers had the best balanced accuracy for predicting hypertrophy (0.78±0.08), injury (0.73±0.10) and proliferative lesions (0.72±0.09). Though chemical and bioactivity class

Multi-resolution cell orientation congruence descriptors for epithelium segmentation in endometrial histology images.

PubMed

Li, Guannan; Raza, Shan E Ahmed; Rajpoot, Nasir M

2017-04-01

It has been recently shown that recurrent miscarriage can be caused by abnormally high ratio of number of uterine natural killer (UNK) cells to the number of stromal cells in human female uterus lining. Due to high workload, the counting of UNK and stromal cells needs to be automated using computer algorithms. However, stromal cells are very similar in appearance to epithelial cells which must be excluded in the counting process. To exclude the epithelial cells from the counting process it is necessary to identify epithelial regions. There are two types of epithelial layers that can be encountered in the endometrium: luminal epithelium and glandular epithelium. To the best of our knowledge, there is no existing method that addresses the segmentation of both types of epithelium simultaneously in endometrial histology images. In this paper, we propose a multi-resolution Cell Orientation Congruence (COCo) descriptor which exploits the fact that neighbouring epithelial cells exhibit similarity in terms of their orientations. Our experimental results show that the proposed descriptors yield accurate results in simultaneously segmenting both luminal and glandular epithelium. Copyright © 2017 Elsevier B.V. All rights reserved.

RED: a set of molecular descriptors based on Renyi entropy.

PubMed

Delgado-Soler, Laura; Toral, Raul; Tomás, M Santos; Rubio-Martinez, Jaime

2009-11-01

New molecular descriptors, RED (Renyi entropy descriptors), based on the generalized entropies introduced by Renyi are presented. Topological descriptors based on molecular features have proven to be useful for describing molecular profiles. Renyi entropy is used as a variability measure to contract a feature-pair distribution composing the descriptor vector. The performance of RED descriptors was tested for the analysis of different sets of molecular distances, virtual screening, and pharmacological profiling. A free parameter of the Renyi entropy has been optimized for all the considered applications.

Learning Careers/Learning Trajectories. Trends and Issues Alert.

ERIC Educational Resources Information Center

Kerka, Sandra

"Learning autobiography,""learning career," and "learning trajectory" are related descriptors for the process of developing attitudes toward learning and the origins of interests, learning styles, and learning processes. The learning career is composed of events, activities, and interpretations that develop individual…

Predicting highly-connected hubs in protein interaction networks by QSAR and biological data descriptors

PubMed Central

Hsing, Michael; Byler, Kendall; Cherkasov, Artem

2009-01-01

Hub proteins (those engaged in most physical interactions in a protein interaction network (PIN) have recently gained much research interest due to their essential role in mediating cellular processes and their potential therapeutic value. It is straightforward to identify hubs if the underlying PIN is experimentally determined; however, theoretical hub prediction remains a very challenging task, as physicochemical properties that differentiate hubs from less connected proteins remain mostly uncharacterized. To adequately distinguish hubs from non-hub proteins we have utilized over 1300 protein descriptors, some of which represent QSAR (quantitative structure-activity relationship) parameters, and some reflect sequence-derived characteristics of proteins including domain composition and functional annotations. Those protein descriptors, together with available protein interaction data have been processed by a machine learning method (boosting trees) and resulted in the development of hub classifiers that are capable of predicting highly interacting proteins for four model organisms: Escherichia coli, Saccharomyces cerevisiae, Drosophila melanogaster and Homo sapiens. More importantly, through the analyses of the most relevant protein descriptors, we are able to demonstrate that hub proteins not only share certain common physicochemical and structural characteristics that make them different from non-hub counterparts, but they also exhibit species-specific characteristics that should be taken into account when analyzing different PINs. The developed prediction models can be used for determining highly interacting proteins in the four studied species to assist future proteomics experiments and PIN analyses. Availability The source code and executable program of the hub classifier are available for download at: http://www.cnbi2.ca/hub-analysis/ PMID:20198194

World Epidemiology Review, Number 105.

DTIC Science & Technology

1978-09-13

human , animal, and plant diseases, insect pests and control, sanitation conditions, immunization and public health programs. 17. Key Words and...Document Analysis. 17a. Descriptors Worldwide Clinical Medicine Environmental Biology Hygiene and Sanitation Microbiology 17b. Identifiers /Open...KIV. ••71) THIS FORM MAY BE REPRODUCED USCOMM-OC UM1-*T1 JPRS 71863 13 September 19 78 WORLD EPIDEMIOLOGY REVIEW No. 105 CONTENTS PAGE HUMAN

Selection of morphoagronomic descriptors for the characterization of accessions of cassava of the Eastern Brazilian Amazon.

PubMed

Silva, R S; Moura, E F; Farias-Neto, J T; Ledo, C A S; Sampaio, J E

2017-04-13

The aim of this study was to select morphoagronomic descriptors to characterize cassava accessions representative of Eastern Brazilian Amazonia. It was characterized 262 accessions using 21 qualitative descriptors. The multiple-correspondence analysis (MCA) technique was applied using the criteria: contribution of the descriptor in the last factorial axis of analysis in successive cycles (SMCA); reverse order of the descriptor's contribution in the last factorial axis of analysis with all descriptors ('O'´p') of Jolliffe's method; mean of the contribution orders of the descriptor in the first three factorial axes in the analysis with all descriptors ('Os') together with ('O'´p'); and order of contribution of weighted mean in the first three factorial axes in the analysis of all descriptors ('Oz'). The dissimilarity coefficient was measured by the method of multicategorical variables. The correlation among the matrix generated with all descriptors and matrices based on each criteria varied (r = 0.21, r = 0.97, r = 0.98, r = 0.13 for SMCA, 'Os', 'Oz' and 'O'´p', respectively). The least informative descriptors were discarded independently and according to both 'Os' and 'Oz' criteria. Thirteen descriptors were capable to discriminate the accessions and to represent the morphological variability of accessions sampled in Brazilian Eastern Amazonia: color of apical leaves, petiole color, color of stem exterior, external color of storage root, color of stem cortex, color of root pulp, texture of root epidermis, color of leaf vein, color of stem epidermis, color of end branches of adult plant, branching habit, root shape, and constriction of root.

A comparison between space-time video descriptors

NASA Astrophysics Data System (ADS)

Costantini, Luca; Capodiferro, Licia; Neri, Alessandro

2013-02-01

The description of space-time patches is a fundamental task in many applications such as video retrieval or classification. Each space-time patch can be described by using a set of orthogonal functions that represent a subspace, for example a sphere or a cylinder, within the patch. In this work, our aim is to investigate the differences between the spherical descriptors and the cylindrical descriptors. In order to compute the descriptors, the 3D spherical and cylindrical Zernike polynomials are employed. This is important because both the functions are based on the same family of polynomials, and only the symmetry is different. Our experimental results show that the cylindrical descriptor outperforms the spherical descriptor. However, the performances of the two descriptors are similar.

Structural alignment of protein descriptors - a combinatorial model.

PubMed

Antczak, Maciej; Kasprzak, Marta; Lukasiak, Piotr; Blazewicz, Jacek

2016-09-17

Structural alignment of proteins is one of the most challenging problems in molecular biology. The tertiary structure of a protein strictly correlates with its function and computationally predicted structures are nowadays a main premise for understanding the latter. However, computationally derived 3D models often exhibit deviations from the native structure. A way to confirm a model is a comparison with other structures. The structural alignment of a pair of proteins can be defined with the use of a concept of protein descriptors. The protein descriptors are local substructures of protein molecules, which allow us to divide the original problem into a set of subproblems and, consequently, to propose a more efficient algorithmic solution. In the literature, one can find many applications of the descriptors concept that prove its usefulness for insight into protein 3D structures, but the proposed approaches are presented rather from the biological perspective than from the computational or algorithmic point of view. Efficient algorithms for identification and structural comparison of descriptors can become crucial components of methods for structural quality assessment as well as tertiary structure prediction. In this paper, we propose a new combinatorial model and new polynomial-time algorithms for the structural alignment of descriptors. The model is based on the maximum-size assignment problem, which we define here and prove that it can be solved in polynomial time. We demonstrate suitability of this approach by comparison with an exact backtracking algorithm. Besides a simplification coming from the combinatorial modeling, both on the conceptual and complexity level, we gain with this approach high quality of obtained results, in terms of 3D alignment accuracy and processing efficiency. All the proposed algorithms were developed and integrated in a computationally efficient tool descs-standalone, which allows the user to identify and structurally compare descriptors of biological molecules, such as proteins and RNAs. Both PDB (Protein Data Bank) and mmCIF (macromolecular Crystallographic Information File) formats are supported. The proposed tool is available as an open source project stored on GitHub ( https://github.com/mantczak/descs-standalone ).

Physicochemical descriptors of aromatic character and their use in drug discovery.

PubMed

Ritchie, Timothy J; Macdonald, Simon J F

2014-09-11

Published physicochemical descriptors of molecules that convey aromaticity-related character are reviewed in the context of drug design and discovery. Studies that have employed aromatic descriptors are discussed, and several descriptors are compared and contrasted.

QSAR modeling of cumulative environmental end-points for the prioritization of hazardous chemicals.

PubMed

Gramatica, Paola; Papa, Ester; Sangion, Alessandro

2018-01-24

The hazard of chemicals in the environment is inherently related to the molecular structure and derives simultaneously from various chemical properties/activities/reactivities. Models based on Quantitative Structure Activity Relationships (QSARs) are useful to screen, rank and prioritize chemicals that may have an adverse impact on humans and the environment. This paper reviews a selection of QSAR models (based on theoretical molecular descriptors) developed for cumulative multivariate endpoints, which were derived by mathematical combination of multiple effects and properties. The cumulative end-points provide an integrated holistic point of view to address environmentally relevant properties of chemicals.

Developing a CD-CBM Anticipatory Approach for Cavitation - Defining a Model-Based Descriptor Consistent Across Processes, Phase 1 Final Report Context-Dependent Prognostics and Health Assessment: A New Paradigm for Condition-based Maintenance SBIR Topic No. N98-114

DOE Office of Scientific and Technical Information (OSTI.GOV)

Allgood, G.O.; Dress, W.B.; Kercel, S.W.

1999-06-01

The objective of this research, and subsequent testing, was to identify specific features of cavitation that could be used as a model-based descriptor in a context-dependent condition-based maintenance (CD-CBM) anticipatory prognostic and health assessment model. This descriptor is based on the physics of the phenomena, capturing the salient features of the process dynamics. The test methodology and approach were developed to make the cavitation features the dominant effect in the process and collected signatures. This would allow the accurate characterization of the salient cavitation features at different operational states. By developing such an abstraction, these attributes can be used asmore » a general diagnostic for a system or any of its components. In this study, the particular focus will be pumps. As many as 90% of pump failures are catastrophic. They seem to be operating normally and fail abruptly without warning. This is true whether the failure is sudden hardware damage requiring repair, such as a gasket failure, or a transition into an undesired operating mode, such as cavitation. This means that conventional diagnostic methods fail to predict 90% of incipient failures and that in addressing this problem, model-based methods can add value where it is actually needed.« less

Towards better modelling of drug-loading in solid lipid nanoparticles: Molecular dynamics, docking experiments and Gaussian Processes machine learning.

PubMed

Hathout, Rania M; Metwally, Abdelkader A

2016-11-01

This study represents one of the series applying computer-oriented processes and tools in digging for information, analysing data and finally extracting correlations and meaningful outcomes. In this context, binding energies could be used to model and predict the mass of loaded drugs in solid lipid nanoparticles after molecular docking of literature-gathered drugs using MOE® software package on molecularly simulated tripalmitin matrices using GROMACS®. Consequently, Gaussian processes as a supervised machine learning artificial intelligence technique were used to correlate the drugs' descriptors (e.g. M.W., xLogP, TPSA and fragment complexity) with their molecular docking binding energies. Lower percentage bias was obtained compared to previous studies which allows the accurate estimation of the loaded mass of any drug in the investigated solid lipid nanoparticles by just projecting its chemical structure to its main features (descriptors). Copyright © 2016 Elsevier B.V. All rights reserved.

The great descriptor melting pot: mixing descriptors for the common good of QSAR models.

PubMed

Tseng, Yufeng J; Hopfinger, Anton J; Esposito, Emilio Xavier

2012-01-01

The usefulness and utility of QSAR modeling depends heavily on the ability to estimate the values of molecular descriptors relevant to the endpoints of interest followed by an optimized selection of descriptors to form the best QSAR models from a representative set of the endpoints of interest. The performance of a QSAR model is directly related to its molecular descriptors. QSAR modeling, specifically model construction and optimization, has benefited from its ability to borrow from other unrelated fields, yet the molecular descriptors that form QSAR models have remained basically unchanged in both form and preferred usage. There are many types of endpoints that require multiple classes of descriptors (descriptors that encode 1D through multi-dimensional, 4D and above, content) needed to most fully capture the molecular features and interactions that contribute to the endpoint. The advantages of QSAR models constructed from multiple, and different, descriptor classes have been demonstrated in the exploration of markedly different, and principally biological systems and endpoints. Multiple examples of such QSAR applications using different descriptor sets are described and that examined. The take-home-message is that a major part of the future of QSAR analysis, and its application to modeling biological potency, ADME-Tox properties, general use in virtual screening applications, as well as its expanding use into new fields for building QSPR models, lies in developing strategies that combine and use 1D through nD molecular descriptors.

Evaluation of vegetation post-fire resilience in the Alpine region using descriptors derived from MODIS spectral index time series

NASA Astrophysics Data System (ADS)

Di Mauro, Biagio; Fava, Francesco; Busetto, Lorenzo; Crosta, Giovanni Franco; Colombo, Roberto

2013-04-01

In this study a method based on the analysis of MODerate-resolution Imaging Spectroradiometer (MODIS) time series is proposed to estimate the post-fire resilience of mountain vegetation (broadleaf forest and prairies) in the Italian Alps. Resilience is defined herewith as the ability of a dynamical system to counteract disturbances. It can be quantified by the amount of time the disturbed system takes to resume, in statistical terms, an ecological functionality comparable with its undisturbed behavior. Satellite images of the Normalized Difference Vegetation Index (NDVI) and of the Enhanced Vegetation Index (EVI) with spatial resolution of 250m and temporal resolution of 16 days in the 2000-2012 time period were used. Wildfire affected areas in the Lombardy region between the years 2000 and 2010 were analysed. Only large fires (affected area >40ha) were selected. For each burned area, an undisturbed adjacent control site was located. Data pre-processing consisted in the smoothing of MODIS time series for noise removal and then a double logistic function was fitted. Land surface phenology descriptors (proxies for growing season start/end/length and green biomass) were extracted in order to characterize the time evolution of the vegetation. Descriptors from a burned area were compared to those extracted from the respective control site by means of the one-way analysis of variance. According to the number of subsequent years which exhibit statistically meaningful difference between burned and control site, five classes of resilience were identified and a set of thematic maps was created for each descriptor. The same method was applied to all 84 aggregated events and to events aggregated by main land cover. EVI index results more sensitive to fire impact than NDVI index. Analysis shows that fire causes both a reduction of the biomass and a variation in the phenology of the Alpine vegetation. Results suggest an average ecosystem resilience of 6-7 years. Moreover, broadleaf forest and prairies show different post-fire behavior in terms of land surface phenology descriptors. In addition to the above analysis, another method is proposed, which derives from the qualitative theory of dynamical systems. The (time dependent) spectral index of a burned area over the period of one year was plotted against its counterpart from the control site. Yearly plots (or scattergrams) before and after the fire were obtained. Each plot is a sequence of points on the plane, which are the vertices of a generally self-intersecting polygonal chain. Some geometrical descriptors were obtained from the yearly chains of each fire. Principal Components Analysis (PCA) of geometrical descriptors was applied to a set of case studies and the obtained results provide a system dynamics interpretation of the natural process.

Simple idea to generate fragment and pharmacophore descriptors and their implications in chemical informatics.

PubMed

Catana, Cornel

2009-03-01

Using a well-defined set of fragments/pharmacophores, a new methodology to calculate fragment/ pharmacophore descriptors for any molecule onto which at least one fragment/pharmacophore can be mapped is presented. To each fragment/pharmacophore present in a molecule, we attach a descriptor that is calculated by identifying the molecule's atoms onto which it maps and summing over its constituent atomic descriptors. The attached descriptors are named C-fragment/pharmacophore descriptors, and this methodology can be applied to any descriptors defined at the atomic level, such as the partition coefficient, molar refractivity, electrotopological state, etc. By using this methodology, the same fragment/pharmacophore can be shown to have different values in different molecules resulting in better discrimination power. As we know, fragment and pharmacophore fingerprints have a lot of applications in chemical informatics. This study has attempted to find the impact of replacing the traditional value of "1" in a fingerprint with real numbers derived form C-fragment/pharmacophore descriptors. One way to do this is to assess the utility of C-fragment/ pharmacophore descriptors in modeling different end points. Here, we exemplify with data from CYP and hERG. The fact that, in many cases, the obtained models were fairly successful and C-fragment descriptors were ranked among the top ones supports the idea that they play an important role in correlation. When we modeled hERG with C-pharmacophore descriptors, however, the model performances decreased slightly, and we attribute this, mainly to the fact that there is no technique capable of handling multiple instances (states). We hope this will open new research, especially in the emerging field of machine learning. Further research is needed to see the impact of C-fragment/pharmacophore descriptors in similarity/dissimilarity applications.

Systems Biological Approach of Molecular Descriptors Connectivity: Optimal Descriptors for Oral Bioavailability Prediction

PubMed Central

Ahmed, Shiek S. S. J.; Ramakrishnan, V.

2012-01-01

Background Poor oral bioavailability is an important parameter accounting for the failure of the drug candidates. Approximately, 50% of developing drugs fail because of unfavorable oral bioavailability. In silico prediction of oral bioavailability (%F) based on physiochemical properties are highly needed. Although many computational models have been developed to predict oral bioavailability, their accuracy remains low with a significant number of false positives. In this study, we present an oral bioavailability model based on systems biological approach, using a machine learning algorithm coupled with an optimal discriminative set of physiochemical properties. Results The models were developed based on computationally derived 247 physicochemical descriptors from 2279 molecules, among which 969, 605 and 705 molecules were corresponds to oral bioavailability, intestinal absorption (HIA) and caco-2 permeability data set, respectively. The partial least squares discriminate analysis showed 49 descriptors of HIA and 50 descriptors of caco-2 are the major contributing descriptors in classifying into groups. Of these descriptors, 47 descriptors were commonly associated to HIA and caco-2, which suggests to play a vital role in classifying oral bioavailability. To determine the best machine learning algorithm, 21 classifiers were compared using a bioavailability data set of 969 molecules with 47 descriptors. Each molecule in the data set was represented by a set of 47 physiochemical properties with the functional relevance labeled as (+bioavailability/−bioavailability) to indicate good-bioavailability/poor-bioavailability molecules. The best-performing algorithm was the logistic algorithm. The correlation based feature selection (CFS) algorithm was implemented, which confirms that these 47 descriptors are the fundamental descriptors for oral bioavailability prediction. Conclusion The logistic algorithm with 47 selected descriptors correctly predicted the oral bioavailability, with a predictive accuracy of more than 71%. Overall, the method captures the fundamental molecular descriptors, that can be used as an entity to facilitate prediction of oral bioavailability. PMID:22815781

Systems biological approach of molecular descriptors connectivity: optimal descriptors for oral bioavailability prediction.

PubMed

Ahmed, Shiek S S J; Ramakrishnan, V

2012-01-01

Poor oral bioavailability is an important parameter accounting for the failure of the drug candidates. Approximately, 50% of developing drugs fail because of unfavorable oral bioavailability. In silico prediction of oral bioavailability (%F) based on physiochemical properties are highly needed. Although many computational models have been developed to predict oral bioavailability, their accuracy remains low with a significant number of false positives. In this study, we present an oral bioavailability model based on systems biological approach, using a machine learning algorithm coupled with an optimal discriminative set of physiochemical properties. The models were developed based on computationally derived 247 physicochemical descriptors from 2279 molecules, among which 969, 605 and 705 molecules were corresponds to oral bioavailability, intestinal absorption (HIA) and caco-2 permeability data set, respectively. The partial least squares discriminate analysis showed 49 descriptors of HIA and 50 descriptors of caco-2 are the major contributing descriptors in classifying into groups. Of these descriptors, 47 descriptors were commonly associated to HIA and caco-2, which suggests to play a vital role in classifying oral bioavailability. To determine the best machine learning algorithm, 21 classifiers were compared using a bioavailability data set of 969 molecules with 47 descriptors. Each molecule in the data set was represented by a set of 47 physiochemical properties with the functional relevance labeled as (+bioavailability/-bioavailability) to indicate good-bioavailability/poor-bioavailability molecules. The best-performing algorithm was the logistic algorithm. The correlation based feature selection (CFS) algorithm was implemented, which confirms that these 47 descriptors are the fundamental descriptors for oral bioavailability prediction. The logistic algorithm with 47 selected descriptors correctly predicted the oral bioavailability, with a predictive accuracy of more than 71%. Overall, the method captures the fundamental molecular descriptors, that can be used as an entity to facilitate prediction of oral bioavailability.

A contour-based shape descriptor for biomedical image classification and retrieval

NASA Astrophysics Data System (ADS)

You, Daekeun; Antani, Sameer; Demner-Fushman, Dina; Thoma, George R.

2013-12-01

Contours, object blobs, and specific feature points are utilized to represent object shapes and extract shape descriptors that can then be used for object detection or image classification. In this research we develop a shape descriptor for biomedical image type (or, modality) classification. We adapt a feature extraction method used in optical character recognition (OCR) for character shape representation, and apply various image preprocessing methods to successfully adapt the method to our application. The proposed shape descriptor is applied to radiology images (e.g., MRI, CT, ultrasound, X-ray, etc.) to assess its usefulness for modality classification. In our experiment we compare our method with other visual descriptors such as CEDD, CLD, Tamura, and PHOG that extract color, texture, or shape information from images. The proposed method achieved the highest classification accuracy of 74.1% among all other individual descriptors in the test, and when combined with CSD (color structure descriptor) showed better performance (78.9%) than using the shape descriptor alone.

Effect of cultivar and roasting technique on sensory quality of Bierzo roasted pepper.

PubMed

Guerra, Marcos; Sanz, Miguel A; Valenciano, José B; Casquero, Pedro A

2011-10-01

Pepper (Capsicum annuum L.) is one of the main horticultural products in the world. Roasted pepper is a high quality transformed product in the Iberian Peninsula, and obtained the recognition of 'Protected Geographical Indication' (PGI) of 'Pimiento Asado del Bierzo' in 2002. Roasted pepper has been traditionally processed with a steel-sheet hob. However, there are no data available about the effect of roasting technique in the quality of roasted pepper. The objective of this work was to compare the sensory quality of roasted pepper using industrial roasting techniques. Sensory properties that showed significant differences between roasting techniques were colour, thickness and charred remains (appearance descriptors), bitterness (taste descriptor) and smokiness (after-taste descriptor). Higher value of descriptors such as colour, charred remains and smokiness for peppers elaborated in a rotary oven, helped roasted pepper to reach a higher level of overall quality, although rotary oven samples reached the lowest roast yield. Roasting technique, rather than landrace, had the greatest effect on the sensory quality of roasted pepper, so the rotary oven was the roasting technique that achieved the highest quality score. This will contribute to improve sensory quality and marketing of PGI 'Pimiento Asado del Bierzo' in high quality markets. Copyright © 2011 Society of Chemical Industry.

Genetic algorithm applied to the selection of factors in principal component-artificial neural networks: application to QSAR study of calcium channel antagonist activity of 1,4-dihydropyridines (nifedipine analogous).

PubMed

Hemmateenejad, Bahram; Akhond, Morteza; Miri, Ramin; Shamsipur, Mojtaba

2003-01-01

A QSAR algorithm, principal component-genetic algorithm-artificial neural network (PC-GA-ANN), has been applied to a set of newly synthesized calcium channel blockers, which are of special interest because of their role in cardiac diseases. A data set of 124 1,4-dihydropyridines bearing different ester substituents at the C-3 and C-5 positions of the dihydropyridine ring and nitroimidazolyl, phenylimidazolyl, and methylsulfonylimidazolyl groups at the C-4 position with known Ca(2+) channel binding affinities was employed in this study. Ten different sets of descriptors (837 descriptors) were calculated for each molecule. The principal component analysis was used to compress the descriptor groups into principal components. The most significant descriptors of each set were selected and used as input for the ANN. The genetic algorithm (GA) was used for the selection of the best set of extracted principal components. A feed forward artificial neural network with a back-propagation of error algorithm was used to process the nonlinear relationship between the selected principal components and biological activity of the dihydropyridines. A comparison between PC-GA-ANN and routine PC-ANN shows that the first model yields better prediction ability.

New Fukui, dual and hyper-dual kernels as bond reactivity descriptors.

PubMed

Franco-Pérez, Marco; Polanco-Ramírez, Carlos-A; Ayers, Paul W; Gázquez, José L; Vela, Alberto

2017-06-21

We define three new linear response indices with promising applications for bond reactivity using the mathematical framework of τ-CRT (finite temperature chemical reactivity theory). The τ-Fukui kernel is defined as the ratio between the fluctuations of the average electron density at two different points in the space and the fluctuations in the average electron number and is designed to integrate to the finite-temperature definition of the electronic Fukui function. When this kernel is condensed, it can be interpreted as a site-reactivity descriptor of the boundary region between two atoms. The τ-dual kernel corresponds to the first order response of the Fukui kernel and is designed to integrate to the finite temperature definition of the dual descriptor; it indicates the ambiphilic reactivity of a specific bond and enriches the traditional dual descriptor by allowing one to distinguish between the electron-accepting and electron-donating processes. Finally, the τ-hyper dual kernel is defined as the second-order derivative of the Fukui kernel and is proposed as a measure of the strength of ambiphilic bonding interactions. Although these quantities have never been proposed, our results for the τ-Fukui kernel and for τ-dual kernel can be derived in zero-temperature formulation of the chemical reactivity theory with, among other things, the widely-used parabolic interpolation model.

Optimized spatio-temporal descriptors for real-time fall detection: comparison of support vector machine and Adaboost-based classification

NASA Astrophysics Data System (ADS)

Charfi, Imen; Miteran, Johel; Dubois, Julien; Atri, Mohamed; Tourki, Rached

2013-10-01

We propose a supervised approach to detect falls in a home environment using an optimized descriptor adapted to real-time tasks. We introduce a realistic dataset of 222 videos, a new metric allowing evaluation of fall detection performance in a video stream, and an automatically optimized set of spatio-temporal descriptors which fed a supervised classifier. We build the initial spatio-temporal descriptor named STHF using several combinations of transformations of geometrical features (height and width of human body bounding box, the user's trajectory with her/his orientation, projection histograms, and moments of orders 0, 1, and 2). We study the combinations of usual transformations of the features (Fourier transform, wavelet transform, first and second derivatives), and we show experimentally that it is possible to achieve high performance using support vector machine and Adaboost classifiers. Automatic feature selection allows to show that the best tradeoff between classification performance and processing time is obtained by combining the original low-level features with their first derivative. Hence, we evaluate the robustness of the fall detection regarding location changes. We propose a realistic and pragmatic protocol that enables performance to be improved by updating the training in the current location with normal activities records.

Advance in ERG Analysis: From Peak Time and Amplitude to Frequency, Power, and Energy

PubMed Central

Lina, Jean-Marc; Lachapelle, Pierre

2014-01-01

Purpose. To compare time domain (TD: peak time and amplitude) analysis of the human photopic electroretinogram (ERG) with measures obtained in the frequency domain (Fourier analysis: FA) and in the time-frequency domain (continuous (CWT) and discrete (DWT) wavelet transforms). Methods. Normal ERGs (n = 40) were analyzed using traditional peak time and amplitude measurements of the a- and b-waves in the TD and descriptors extracted from FA, CWT, and DWT. Selected descriptors were also compared in their ability to monitor the long-term consequences of disease process. Results. Each method extracted relevant information but had distinct limitations (i.e., temporal and frequency resolutions). The DWT offered the best compromise by allowing us to extract more relevant descriptors of the ERG signal at the cost of lesser temporal and frequency resolutions. Follow-ups of disease progression were more prolonged with the DWT (max 29 years compared to 13 with TD). Conclusions. Standardized time domain analysis of retinal function should be complemented with advanced DWT descriptors of the ERG. This method should allow more sensitive/specific quantifications of ERG responses, facilitate follow-up of disease progression, and identify diagnostically significant changes of ERG waveforms that are not resolved when the analysis is only limited to time domain measurements. PMID:25061605

Early diagnostic of concurrent gear degradation processes progressing under time-varying loads

NASA Astrophysics Data System (ADS)

Guilbault, Raynald; Lalonde, Sébastien

2016-08-01

This study develops a gear diagnostic procedure for the detection of multi- and concurrent degradation processes evolving under time-varying loads. Instead of a conventional comparison between a descriptor and an alarm level, this procedure bases its detection strategy on a descriptor evolution tracking; a lasting descriptor increase denotes the presence of ongoing degradation mechanisms. The procedure works from time domain residual signals prepared in the frequency domain, and accepts any gear conditions as reference signature. To extract the load fluctuation repercussions, the procedure integrates a scaling factor. The investigation first examines a simplification assuming a linear connection between the load and the dynamic response amplitudes. However, while generally valuable, the precision losses associated with large load variations may mask the contribution of tiny flaws. To better reflect the real non-linear relation, the paper reformulates the scaling factor; a power law with an exponent value of 0.85 produces noticeable improvements of the load effect extraction. To reduce the consequences of remaining oscillations, the procedure also includes a filtering phase. During the validation program, a synthetic wear progression assuming a commensurate relation between the wear depth and friction assured controlled evolutions of the surface degradation influence, whereas the fillet crack growth remained entirely determined by the operation conditions. Globally, the tested conditions attest that the final strategy provides accurate monitoring of coexisting isolated damages and general surface deterioration, and that its tracking-detection capacities are unaffected by severe time variations of external loads. The procedure promptly detects the presence of evolving abnormal phenomena. The tests show that the descriptor curve shapes virtually describe the constant wear progression superimposed on the crack length evolution. At the tooth fracture, the mean values of the residual signal evince strong perturbations, while after this episode, the monitoring curves continue signaling the ongoing wear process.

An effective content-based image retrieval technique for image visuals representation based on the bag-of-visual-words model

PubMed Central

Jabeen, Safia; Mehmood, Zahid; Mahmood, Toqeer; Saba, Tanzila; Rehman, Amjad; Mahmood, Muhammad Tariq

2018-01-01

For the last three decades, content-based image retrieval (CBIR) has been an active research area, representing a viable solution for retrieving similar images from an image repository. In this article, we propose a novel CBIR technique based on the visual words fusion of speeded-up robust features (SURF) and fast retina keypoint (FREAK) feature descriptors. SURF is a sparse descriptor whereas FREAK is a dense descriptor. Moreover, SURF is a scale and rotation-invariant descriptor that performs better in the case of repeatability, distinctiveness, and robustness. It is robust to noise, detection errors, geometric, and photometric deformations. It also performs better at low illumination within an image as compared to the FREAK descriptor. In contrast, FREAK is a retina-inspired speedy descriptor that performs better for classification-based problems as compared to the SURF descriptor. Experimental results show that the proposed technique based on the visual words fusion of SURF-FREAK descriptors combines the features of both descriptors and resolves the aforementioned issues. The qualitative and quantitative analysis performed on three image collections, namely Corel-1000, Corel-1500, and Caltech-256, shows that proposed technique based on visual words fusion significantly improved the performance of the CBIR as compared to the feature fusion of both descriptors and state-of-the-art image retrieval techniques. PMID:29694429

An effective content-based image retrieval technique for image visuals representation based on the bag-of-visual-words model.

PubMed

Jabeen, Safia; Mehmood, Zahid; Mahmood, Toqeer; Saba, Tanzila; Rehman, Amjad; Mahmood, Muhammad Tariq

2018-01-01

For the last three decades, content-based image retrieval (CBIR) has been an active research area, representing a viable solution for retrieving similar images from an image repository. In this article, we propose a novel CBIR technique based on the visual words fusion of speeded-up robust features (SURF) and fast retina keypoint (FREAK) feature descriptors. SURF is a sparse descriptor whereas FREAK is a dense descriptor. Moreover, SURF is a scale and rotation-invariant descriptor that performs better in the case of repeatability, distinctiveness, and robustness. It is robust to noise, detection errors, geometric, and photometric deformations. It also performs better at low illumination within an image as compared to the FREAK descriptor. In contrast, FREAK is a retina-inspired speedy descriptor that performs better for classification-based problems as compared to the SURF descriptor. Experimental results show that the proposed technique based on the visual words fusion of SURF-FREAK descriptors combines the features of both descriptors and resolves the aforementioned issues. The qualitative and quantitative analysis performed on three image collections, namely Corel-1000, Corel-1500, and Caltech-256, shows that proposed technique based on visual words fusion significantly improved the performance of the CBIR as compared to the feature fusion of both descriptors and state-of-the-art image retrieval techniques.

Quantitative structure-retention relationships for gas chromatographic retention indices of alkylbenzenes with molecular graph descriptors.

PubMed

Ivanciuc, O; Ivanciuc, T; Klein, D J; Seitz, W A; Balaban, A T

2001-02-01

Quantitative structure-retention relationships (QSRR) represent statistical models that quantify the connection between the molecular structure and the chromatographic retention indices of organic compounds, allowing the prediction of retention indices of novel, not yet synthesized compounds, solely from their structural descriptors. Using multiple linear regression, QSRR models for the gas chromatographic Kováts retention indices of 129 alkylbenzenes are generated using molecular graph descriptors. The correlational ability of structural descriptors computed from 10 molecular matrices is investigated, showing that the novel reciprocal matrices give numerical indices with improved correlational ability. A QSRR equation with 5 graph descriptors gives the best calibration and prediction results, demonstrating the usefulness of the molecular graph descriptors in modeling chromatographic retention parameters. The sequential orthogonalization of descriptors suggests simpler QSRR models by eliminating redundant structural information.

Endocrine Profiling and Prioritization of Environmental Chemicals Using ToxCast Data

PubMed Central

Reif, David M.; Martin, Matthew T.; Tan, Shirlee W.; Houck, Keith A.; Judson, Richard S.; Richard, Ann M.; Knudsen, Thomas B.; Dix, David J.; Kavlock, Robert J.

2010-01-01

Background The prioritization of chemicals for toxicity testing is a primary goal of the U.S. Environmental Protection Agency (EPA) ToxCast™ program. Phase I of ToxCast used a battery of 467 in vitro, high-throughput screening assays to assess 309 environmental chemicals. One important mode of action leading to toxicity is endocrine disruption, and the U.S. EPA’s Endocrine Disruptor Screening Program (EDSP) has been charged with screening pesticide chemicals and environmental contaminants for their potential to affect the endocrine systems of humans and wildlife. Objective The goal of this study was to develop a flexible method to facilitate the rational prioritization of chemicals for further evaluation and demonstrate its application as a candidate decision-support tool for EDSP. Methods Focusing on estrogen, androgen, and thyroid pathways, we defined putative endocrine profiles and derived a relative rank or score for the entire ToxCast library of 309 unique chemicals. Effects on other nuclear receptors and xenobiotic metabolizing enzymes were also considered, as were pertinent chemical descriptors and pathways relevant to endocrine-mediated signaling. Results Combining multiple data sources into an overall, weight-of-evidence Toxicological Priority Index (ToxPi) score for prioritizing further chemical testing resulted in more robust conclusions than any single data source taken alone. Conclusions Incorporating data from in vitro assays, chemical descriptors, and biological pathways in this prioritization schema provided a flexible, comprehensive visualization and ranking of each chemical’s potential endocrine activity. Importantly, ToxPi profiles provide a transparent visualization of the relative contribution of all information sources to an overall priority ranking. The method developed here is readily adaptable to diverse chemical prioritization tasks. PMID:20826373

ChemoPy: freely available python package for computational biology and chemoinformatics.

PubMed

Cao, Dong-Sheng; Xu, Qing-Song; Hu, Qian-Nan; Liang, Yi-Zeng

2013-04-15

Molecular representation for small molecules has been routinely used in QSAR/SAR, virtual screening, database search, ranking, drug ADME/T prediction and other drug discovery processes. To facilitate extensive studies of drug molecules, we developed a freely available, open-source python package called chemoinformatics in python (ChemoPy) for calculating the commonly used structural and physicochemical features. It computes 16 drug feature groups composed of 19 descriptors that include 1135 descriptor values. In addition, it provides seven types of molecular fingerprint systems for drug molecules, including topological fingerprints, electro-topological state (E-state) fingerprints, MACCS keys, FP4 keys, atom pairs fingerprints, topological torsion fingerprints and Morgan/circular fingerprints. By applying a semi-empirical quantum chemistry program MOPAC, ChemoPy can also compute a large number of 3D molecular descriptors conveniently. The python package, ChemoPy, is freely available via http://code.google.com/p/pychem/downloads/list, and it runs on Linux and MS-Windows. Supplementary data are available at Bioinformatics online.

Signaling completion of a message transfer from an origin compute node to a target compute node

DOEpatents

Blocksome, Michael A [Rochester, MN; Parker, Jeffrey J [Rochester, MN

2011-05-24

Signaling completion of a message transfer from an origin node to a target node includes: sending, by an origin DMA engine, an RTS message, the RTS message specifying an application message for transfer to the target node from the origin node; receiving, by the origin DMA engine, a remote get message containing a data descriptor for the message and a completion notification descriptor, the completion notification descriptor specifying a local direct put transfer operation for transferring data locally on the origin node; inserting, by the origin DMA engine in an injection FIFO buffer, the data descriptor followed by the completion notification descriptor; transferring, by the origin DMA engine to the target node, the message in dependence upon the data descriptor; and notifying, by the origin DMA engine, the application that transfer of the message is complete in dependence upon the completion notification descriptor.

Signaling completion of a message transfer from an origin compute node to a target compute node

DOEpatents

Blocksome, Michael A [Rochester, MN

2011-02-15

Signaling completion of a message transfer from an origin node to a target node includes: sending, by an origin DMA engine, an RTS message, the RTS message specifying an application message for transfer to the target node from the origin node; receiving, by the origin DMA engine, a remote get message containing a data descriptor for the message and a completion notification descriptor, the completion notification descriptor specifying a local memory FIFO data transfer operation for transferring data locally on the origin node; inserting, by the origin DMA engine in an injection FIFO buffer, the data descriptor followed by the completion notification descriptor; transferring, by the origin DMA engine to the target node, the message in dependence upon the data descriptor; and notifying, by the origin DMA engine, the application that transfer of the message is complete in dependence upon the completion notification descriptor.

Multi-Scale Surface Descriptors

PubMed Central

Cipriano, Gregory; Phillips, George N.; Gleicher, Michael

2010-01-01

Local shape descriptors compactly characterize regions of a surface, and have been applied to tasks in visualization, shape matching, and analysis. Classically, curvature has be used as a shape descriptor; however, this differential property characterizes only an infinitesimal neighborhood. In this paper, we provide shape descriptors for surface meshes designed to be multi-scale, that is, capable of characterizing regions of varying size. These descriptors capture statistically the shape of a neighborhood around a central point by fitting a quadratic surface. They therefore mimic differential curvature, are efficient to compute, and encode anisotropy. We show how simple variants of mesh operations can be used to compute the descriptors without resorting to expensive parameterizations, and additionally provide a statistical approximation for reduced computational cost. We show how these descriptors apply to a number of uses in visualization, analysis, and matching of surfaces, particularly to tasks in protein surface analysis. PMID:19834190

Respiratory complaints in Chinese: cultural and diagnostic specificities.

PubMed

Han, Jiangna; Zhu, Yuanjue; Li, Shunwei; Chen, Xiansheng; Put, Claudia; Van de Woestijne, Karel P; Van den Bergh, Omer

2005-06-01

We investigated the qualitative components of a wide range of Chinese descriptors of dyspnea and associated symptoms, and their relevance for clinical diagnosis. Sixty-one spontaneously reported descriptors were elicited in Chinese patients to make a symptom checklist, which was administered to new groups of patients with different cardiopulmonary diseases, to patients with medically unexplained dyspnea and to healthy subjects. Test-retest reliability was satisfactory for most of the descriptors. A principal component analysis on 61 descriptors yielded the following eight factors: dyspnea-effort of breathing; dyspnea-affective aspect; wheezing; anxiety; tingling; palpitation; coughing and sputum; and dying experience. Although the descriptors of dyspnea-effort of breathing resembled Western wordings and were shared by patients with a variety of diseases, the descriptors of dyspnea-affective aspect appeared to be more culturally specific and were primarily linked to the diagnosis of medically unexplained dyspnea, whereas wheezing was specifically linked to asthma. Three factors of breathlessness were found in Chinese. The descriptors of dyspnea-effort of breathing and wheezing appear to be similar to Western descriptors, whereas the dyspnea-affective aspect seems to bear cultural specificity.

Fast Localization in Large-Scale Environments Using Supervised Indexing of Binary Features.

PubMed

Youji Feng; Lixin Fan; Yihong Wu

2016-01-01

The essence of image-based localization lies in matching 2D key points in the query image and 3D points in the database. State-of-the-art methods mostly employ sophisticated key point detectors and feature descriptors, e.g., Difference of Gaussian (DoG) and Scale Invariant Feature Transform (SIFT), to ensure robust matching. While a high registration rate is attained, the registration speed is impeded by the expensive key point detection and the descriptor extraction. In this paper, we propose to use efficient key point detectors along with binary feature descriptors, since the extraction of such binary features is extremely fast. The naive usage of binary features, however, does not lend itself to significant speedup of localization, since existing indexing approaches, such as hierarchical clustering trees and locality sensitive hashing, are not efficient enough in indexing binary features and matching binary features turns out to be much slower than matching SIFT features. To overcome this, we propose a much more efficient indexing approach for approximate nearest neighbor search of binary features. This approach resorts to randomized trees that are constructed in a supervised training process by exploiting the label information derived from that multiple features correspond to a common 3D point. In the tree construction process, node tests are selected in a way such that trees have uniform leaf sizes and low error rates, which are two desired properties for efficient approximate nearest neighbor search. To further improve the search efficiency, a probabilistic priority search strategy is adopted. Apart from the label information, this strategy also uses non-binary pixel intensity differences available in descriptor extraction. By using the proposed indexing approach, matching binary features is no longer much slower but slightly faster than matching SIFT features. Consequently, the overall localization speed is significantly improved due to the much faster key point detection and descriptor extraction. It is empirically demonstrated that the localization speed is improved by an order of magnitude as compared with state-of-the-art methods, while comparable registration rate and localization accuracy are still maintained.

Dyspnea descriptors developed in Brazil: application in obese patients and in patients with cardiorespiratory diseases.

PubMed

Teixeira, Christiane Aires; Rodrigues Júnior, Antonio Luiz; Straccia, Luciana Cristina; Vianna, Elcio Dos Santos Oliveira; Silva, Geruza Alves da; Martinez, José Antônio Baddini

2011-01-01

To develop a set of descriptive terms applied to the sensation of dyspnea (dyspnea descriptors) for use in Brazil and to investigate the usefulness of these descriptors in four distinct clinical conditions that can be accompanied by dyspnea. We collected 111 dyspnea descriptors from 67 patients and 10 health professionals. These descriptors were analyzed and reduced to 15 based on their frequency of use, similarity of meaning, and potential pathophysiological value. Those 15 descriptors were applied in 50 asthma patients, 50 COPD patients, 30 patients with heart failure, and 50 patients with class II or III obesity. The three best descriptors, as selected by the patients, were studied by cluster analysis. Potential associations between the identified clusters and the four clinical conditions were also investigated. The use of this set of descriptors led to a solution with seven clusters, designated sufoco (suffocating), aperto (tight), rápido (rapid), fadiga (fatigue), abafado (stuffy), trabalho/inspiração (work/inhalation), and falta de ar (shortness of breath). Overlapping of descriptors was quite common among the patients, regardless of their clinical condition. Asthma was significantly associated with the sufoco and trabalho/inspiração clusters, whereas COPD and heart failure were associated with the sufoco, trabalho/inspiração, and falta de ar clusters. Obesity was associated only with the falta de ar cluster. In Brazil, patients who are accustomed to perceiving dyspnea employ various descriptors in order to describe the symptom, and these descriptors can be grouped into similar clusters. In our study sample, such clusters showed no usefulness in differentiating among the four clinical conditions evaluated.

Clustering pesticides according to their molecular properties and their impacts by considering additional ecotoxicological parameters in the TyPol method

NASA Astrophysics Data System (ADS)

Traore, Harouna; Crouzet, Olivier; Mamy, Laure; Sireyjol, Christine; Rossard, Virginie; Servien, Remy; Latrille, Eric; Benoit, Pierre

2017-04-01

The understanding of the fate of pesticides and their environmental impacts largely relies on their molecular properties. We recently developed 'TyPol' (Typology of Pollutants), a clustering method based on statistical analyses combining several environmental endpoints (i.e. environmental parameters such as sorption coefficient, degradation half-life) and one ecotoxicological one (bioconcentration factor), and structural molecular descriptors (number of atoms in the molecule, molecular surface, dipole moment, energy of orbitals…). TyPol has been conceived on the available knowledge on QSAR of a wide diversity of organic compounds (Mamy et al., 2015). This approach also allows to focus on transformation products present in different clusters and to infer possible changes in environmental fate consecutively to different degradation processes (Servien et al., 2014; Benoit et al., 2016). The initial version of TyPol did not include any ecotoxicological parameters except the bioconcentration factor (BCF), which informs more on the transfer along the trophic chain rather than on the effects on non-target organisms. The objective was to implement the TyPol database with a data set of ecotoxicological data concerning pesticides and several aquatic and terrestrial organisms, in order to test the possibility to extend TyPol to ecotoxicological effects on various organisms. The data analysis (available literature and databases) revealed that relevant ecotoxicological endpoints for terrestrial organisms such as soil microorganisms and macroinvertebrates are lacking compared to aquatic organisms. We have added seven parameters for acute (EC50, LC50) and chronic (NOEC) toxicological effects for the following organisms: Daphnia, Algae, Lemna and Earthworm. In this new configuration, TyPol was used to classify about 45 pesticides in different behavioural and ecotoxicity clusters. The clustering results were analyzed to reveals relationships between molecular descriptors, environmental parameters and the added toxicological parameters. Some trends between soil adsorption or Kow coefficient and the acute toxicity towards earthworms or algae were highlighted, and discussed on the basis of the concept of contaminant bioavailability. This proof-of-concept study also showed that the in silico clustering method TyPol can successfully address new questions and can be expanded with other parameters of interest. Keywords: pesticides, toxicity, QSAR, clustering, PLS References : Servien R., Mamy L., Li Z., Rossard V., Latrille E., Bessac F., Patureau D., Benoit P., 2014. TyPol - A new methodology for organic compounds clustering based on their molecular characteristics and environmental behavior. Chemosphere, 111, 613-622. Mamy L., Patureau D., Barriuso E., Bedos C., Bessac F., Louchart X., Martin-Laurent F., Miege C., Benoit P., 2015. Prediction of the fate of organic compounds in the environment from their molecular properties: A review. Critical Reviews in Environmental Science and Technology, 45, 12, 1277-1377 (Open access). Benoit P., Mamy L., Servien R., Li Z., Latrille E., Rossard V., Bessac F., Patureau D., Martin-Laurent F. 2017. Categorizing chlordecone potential degradation products to explore their environmental fate. Science of the Total Environment, 574, 781-795.

Benchmarking of protein descriptor sets in proteochemometric modeling (part 2): modeling performance of 13 amino acid descriptor sets

PubMed Central

2013-01-01

Background While a large body of work exists on comparing and benchmarking descriptors of molecular structures, a similar comparison of protein descriptor sets is lacking. Hence, in the current work a total of 13 amino acid descriptor sets have been benchmarked with respect to their ability of establishing bioactivity models. The descriptor sets included in the study are Z-scales (3 variants), VHSE, T-scales, ST-scales, MS-WHIM, FASGAI, BLOSUM, a novel protein descriptor set (termed ProtFP (4 variants)), and in addition we created and benchmarked three pairs of descriptor combinations. Prediction performance was evaluated in seven structure-activity benchmarks which comprise Angiotensin Converting Enzyme (ACE) dipeptidic inhibitor data, and three proteochemometric data sets, namely (1) GPCR ligands modeled against a GPCR panel, (2) enzyme inhibitors (NNRTIs) with associated bioactivities against a set of HIV enzyme mutants, and (3) enzyme inhibitors (PIs) with associated bioactivities on a large set of HIV enzyme mutants. Results The amino acid descriptor sets compared here show similar performance (<0.1 log units RMSE difference and <0.1 difference in MCC), while errors for individual proteins were in some cases found to be larger than those resulting from descriptor set differences ( > 0.3 log units RMSE difference and >0.7 difference in MCC). Combining different descriptor sets generally leads to better modeling performance than utilizing individual sets. The best performers were Z-scales (3) combined with ProtFP (Feature), or Z-Scales (3) combined with an average Z-Scale value for each target, while ProtFP (PCA8), ST-Scales, and ProtFP (Feature) rank last. Conclusions While amino acid descriptor sets capture different aspects of amino acids their ability to be used for bioactivity modeling is still – on average – surprisingly similar. Still, combining sets describing complementary information consistently leads to small but consistent improvement in modeling performance (average MCC 0.01 better, average RMSE 0.01 log units lower). Finally, performance differences exist between the targets compared thereby underlining that choosing an appropriate descriptor set is of fundamental for bioactivity modeling, both from the ligand- as well as the protein side. PMID:24059743

Indicator Properties of Baltic Zooplankton for Classification of Environmental Status within Marine Strategy Framework Directive.

PubMed

Gorokhova, Elena; Lehtiniemi, Maiju; Postel, Lutz; Rubene, Gunta; Amid, Callis; Lesutiene, Jurate; Uusitalo, Laura; Strake, Solvita; Demereckiene, Natalja

2016-01-01

The European Marine Strategy Framework Directive requires the EU Member States to estimate the level of anthropogenic impacts on their marine systems using 11 Descriptors. Assessing food web response to altered habitats is addressed by Descriptor 4 and its indicators, which are being developed for regional seas. However, the development of simple foodweb indicators able to assess the health of ecologically diverse, spatially variable and complex interactions is challenging. Zooplankton is a key element in marine foodwebs and thus comprise an important part of overall ecosystem health. Here, we review work on zooplankton indicator development using long-term data sets across the Baltic Sea and report the main findings. A suite of zooplankton community metrics were evaluated as putative ecological indicators that track community state in relation to Good Environmental Status (GES) criteria with regard to eutrophication and fish feeding conditions in the Baltic Sea. On the basis of an operational definition of GES, we propose mean body mass of zooplankton in the community in combination with zooplankton stock measured as either abundance or biomass to be applicable as an integrated indicator that could be used within the Descriptor 4 in the Baltic Sea. These metrics performed best in predicting zooplankton being in-GES when considering all datasets evaluated. However, some other metrics, such as copepod biomass, the contribution of copepods to the total zooplankton biomass or biomass-based Cladocera: Copepoda ratio, were equally reliable or even superior in certain basin-specific assessments. Our evaluation suggests that in several basins of the Baltic Sea, zooplankton communities currently appear to be out-of-GES, being comprised by smaller zooplankters and having lower total abundance or biomass compared to the communities during the reference conditions; however, the changes in the taxonomic structure underlying these trends vary widely across the sea basins due to the estuarine character of the Baltic Sea.

The association between negative self-descriptions and depressive symptomology: does culture make a difference?

PubMed

Saint Arnault, Denise; Sakamoto, Shinji; Moriwaki, Aiko

2005-04-01

Research findings that depressed Americans endorse more negative self-related adjectives than controls may be related to a shared self-enhancement cultural frame. This study examines the relationship between negative core self-descriptors and depressive symptoms in 79 Japanese and 50 American women. Americans had more positive self-descriptions and core self-descriptors; however, there were no cultural group differences in number of negative self-descriptors or core self-descriptors. There was a significant correlation between negative core self-descriptor and Beck Depression Inventory (BDI) for Americans only, explaining 10.6% of the BDI variance. Analysis of variance revealed that there was significant BDI group differences for American negative core self-descriptor only. Theoretical possibilities are discussed.

The Association Between Negative Self-Descriptions and Depressive Symptomology: Does Culture Make a Difference?

PubMed Central

Sakamoto, Shinji; Moriwaki, Aiko

2007-01-01

Research findings that depressed Americans endorse more negative self-related adjectives than controls may be related to a shared self-enhancement cultural frame. This study examines the relationship between negative core self-descriptors and depressive symptoms in 79 Japanese and 50 American women. Americans had more positive self-descriptions and core self-descriptors; however, there were no cultural group differences in number of negative self-descriptors or core self-descriptors. There was a significant correlation between negative core self-descriptor and Beck Depression Inventory (BDI) for Americans only, explaining 10.6% of the BDI variance. Analysis of variance revealed that there was significant BDI group differences for American negative core self-descriptor only. Theoretical possibilities are discussed. PMID:15902678

Completion processing for data communications instructions

DOEpatents

Blocksome, Michael A.; Kumar, Sameer; Parker, Jeffrey J.

2014-06-03

Completion processing of data communications instructions in a distributed computing environment, including receiving, in an active messaging interface (`AMI`) data communications instructions, at least one instruction specifying a callback function; injecting into an injection FIFO buffer of a data communication adapter, an injection descriptor, each slot in the injection FIFO buffer having a corresponding slot in a pending callback list; listing in the pending callback list any callback function specified by an instruction, incrementing a pending callback counter for each listed callback function; transferring payload data as per each injection descriptor, incrementing a transfer counter upon completion of each transfer; determining from counter values whether the pending callback list presently includes callback functions whose data transfers have been completed; calling by the AMI any such callback functions from the pending callback list, decrementing the pending callback counter for each callback function called.

Uterus segmentation in dynamic MRI using LBP texture descriptors

NASA Astrophysics Data System (ADS)

Namias, R.; Bellemare, M.-E.; Rahim, M.; Pirró, N.

2014-03-01

Pelvic floor disorders cover pathologies of which physiopathology is not well understood. However cases get prevalent with an ageing population. Within the context of a project aiming at modelization of the dynamics of pelvic organs, we have developed an efficient segmentation process. It aims at alleviating the radiologist with a tedious one by one image analysis. From a first contour delineating the uterus-vagina set, the organ border is tracked along a dynamic mri sequence. The process combines movement prediction, local intensity and texture analysis and active contour geometry control. Movement prediction allows a contour intitialization for next image in the sequence. Intensity analysis provides image-based local contour detection enhanced by local binary pattern (lbp) texture descriptors. Geometry control prohibits self intersections and smoothes the contour. Results show the efficiency of the method with images produced in clinical routine.

Influence of Interpretation Aids on Attentional Capture, Visual Processing, and Understanding of Front-of-Package Nutrition Labels.

PubMed

Antúnez, Lucía; Giménez, Ana; Maiche, Alejandro; Ares, Gastón

2015-01-01

To study the influence of 2 interpretational aids of front-of-package (FOP) nutrition labels (color code and text descriptors) on attentional capture and consumers' understanding of nutritional information. A full factorial design was used to assess the influence of color code and text descriptors using visual search and eye tracking. Ten trained assessors participated in the visual search study and 54 consumers completed the eye-tracking study. In the visual search study, assessors were asked to indicate whether there was a label high in fat within sets of mayonnaise labels with different FOP labels. In the eye-tracking study, assessors answered a set of questions about the nutritional content of labels. The researchers used logistic regression to evaluate the influence of interpretational aids of FOP nutrition labels on the percentage of correct answers. Analyses of variance were used to evaluate the influence of the studied variables on attentional measures and participants' response times. Response times were significantly higher for monochromatic FOP labels compared with color-coded ones (3,225 vs 964 ms; P < .001), which suggests that color codes increase attentional capture. The highest number and duration of fixations and visits were recorded on labels that did not include color codes or text descriptors (P < .05). The lowest percentage of incorrect answers was observed when the nutrient level was indicated using color code and text descriptors (P < .05). The combination of color codes and text descriptors seems to be the most effective alternative to increase attentional capture and understanding of nutritional information. Copyright © 2015 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

A Short Review of the Generation of Molecular Descriptors and Their Applications in Quantitative Structure Property/Activity Relationships.

PubMed

Sahoo, Sagarika; Adhikari, Chandana; Kuanar, Minati; Mishra, Bijay K

2016-01-01

Synthesis of organic compounds with specific biological activity or physicochemical characteristics needs a thorough analysis of the enumerable data set obtained from literature. Quantitative structure property/activity relationships have made it simple by predicting the structure of the compound with any optimized activity. For that there is a paramount data set of molecular descriptors (MD). This review is a survey on the generation of the molecular descriptors and its probable applications in QSP/AR. Literatures have been collected from a wide class of research journals, citable web reports, seminar proceedings and books. The MDs were classified according to their generation. The applications of the MDs on the QSP/AR have also been reported in this review. The MDs can be classified into experimental and theoretical types, having a sub classification of the later into structural and quantum chemical descriptors. The structural parameters are derived from molecular graphs or topology of the molecules. Even the pixel of the molecular image can be used as molecular descriptor. In QSPR studies the physicochemical properties include boiling point, heat capacity, density, refractive index, molar volume, surface tension, heat of formation, octanol-water partition coefficient, solubility, chromatographic retention indices etc. Among biological activities toxicity, antimalarial activity, sensory irritant, potencies of local anesthetic, tadpole narcosis, antifungal activity, enzyme inhibiting activity are some important parameters in the QSAR studies. The classification of the MDs is mostly generic in nature. The application of the MDs in QSP/AR also has a generic link. Experimental MDs are more suitable in correlation analysis than the theoretical ones but are more expensive for generation. In advent of sophisticated computational tools and experimental design proliferation of MDs is inevitable, but for a highly optimized MD, studies on generation of MD is an unending process.

Regional-scale drivers of marine nematode distribution in Southern Ocean continental shelf sediments

NASA Astrophysics Data System (ADS)

Hauquier, Freija; Verleyen, Elie; Tytgat, Bjorn; Vanreusel, Ann

2018-07-01

Many marine meiofauna taxa seem to possess cosmopolitan species distributions, despite their endobenthic lifestyle and restricted long-distance dispersal capacities. In light of this paradox we used a metacommunity framework to study spatial turnover in free-living nematode distribution and assess the importance of local environmental conditions in explaining differences between communities in surface and subsurface sediments of the Southern Ocean continental shelf. We analysed nematode community structure in two sediment layers (0-3 cm and 3-5 cm) of locations maximum 2400 km apart. We first focused on a subset of locations to evaluate whether the genus level is sufficiently taxonomically fine-grained to study large-scale patterns in nematode community structure. We subsequently used redundancy and variation partitioning analyses to quantify the unique and combined effects of local environmental conditions and spatial descriptors on genus-level community composition. Macroecological patterns in community structure were highly congruent at the genus and species level. Nematode community composition was highly divergent between both depth strata, likely as a result of local abiotic conditions. Variation in community structure between the different regions largely stemmed from turnover (i.e. genus/species replacement) rather than nestedness (i.e. genus/species loss). The level of turnover among communities increased with geographic distance and was more pronounced in subsurface layers compared to surface sediments. Variation partitioning analysis revealed that both environmental and spatial predictors significantly explained variation in community structure. Moreover, the shared fraction of both sets of variables was high, which suggested a substantial amount of spatially structured environmental variation. Additionally, the effect of space independent of environment was much higher than the effect of environment independent of space, which shows the importance of including spatial descriptors in meiofauna and nematode community ecology. Large-scale assessment of free-living nematode diversity and abundance in the Southern Ocean shelf zone revealed strong horizontal and vertical spatial structuring in response to local environmental conditions, in combination with (most likely) dispersal limitation.

Assessing the main threats to marine ecosystem components of the Adriatic - Ionian Region for the implementation of Maritime Spatial Planning

NASA Astrophysics Data System (ADS)

Lipizer, Marina

2015-04-01

Marine and coastal ecosystems and the related benefits they provide for humans are threatened by increasing pressures and competing usages. To address these issues, in the last decade, several EU legislations have been formulated to guarantee and promote sustainable use of the sea (e.g. Common Fishery Policy, Marine Strategy Framework Directive, Maritime Spatial Planning). As a first step to implement cross-border Maritime Spatial Planning (MSP) in the Adriatic - Ionian Seas, a review of the main anthropogenic pressures due to maritime activities involving the Adriatic - Ionian Region (AIR) as well as of the most relevant environmental components has been carried out. The main objective of the analysis is to better identify the spatial distribution of human uses of the sea and of the key environmental components and the ecosystem services provided. The analysis of the existing conditions includes a description of the human activities per economic sector, considering type, location, dimension and magnitude of the activity in the AIR and the spatial extent of the main environmental and ecological values present in the AIR. The environmental status has been characterized according to the descriptors proposed by the Marine Strategy Framework Directive (MSFD Directive 2008/56/EC) and the most sensitive ecosystem components in the AIR have been pointed out. A qualitative analysis of the relationships between good environmental status descriptors sensu MSFD and ecosystem services in the AIR has been carried out to provide useful information for the implementation of MSP. Cross-border Maritime Spatial Planning is particularly needed in a semi-enclosed basin such as the Adriatic Sea, hosting very diverse human activities, ranging from fishery to tourism, sand extraction, commercial and passenger transport, oil and gas exploration and exploitation, which may partially overlap and severely threaten ecosystem functioning and the associated services.

Automated selection of BI-RADS lesion descriptors for reporting calcifications in mammograms

NASA Astrophysics Data System (ADS)

Paquerault, Sophie; Jiang, Yulei; Nishikawa, Robert M.; Schmidt, Robert A.; D'Orsi, Carl J.; Vyborny, Carl J.; Newstead, Gillian M.

2003-05-01

We are developing an automated computer technique to describe calcifications in mammograms according to the BI-RADS lexicon. We evaluated this technique by its agreement with radiologists' description of the same lesions. Three expert mammographers reviewed our database of 90 cases of digitized mammograms containing clustered microcalcifications and described the calcifications according to BI-RADS. In our study, the radiologists used only 4 of the 5 calcification distribution descriptors and 5 of the 14 calcification morphology descriptors contained in BI-RADS. Our computer technique was therefore designed specifically for these 4 calcification distribution descriptors and 5 calcification morphology descriptors. For calcification distribution, 4 linear discriminant analysis (LDA) classifiers were developed using 5 computer-extracted features to produce scores of how well each descriptor describes a cluster. Similarly, for calcification morphology, 5 LDAs were designed using 10 computer-extracted features. We trained the LDAs using only the BI-RADS data reported by the first radiologist and compared the computer output to the descriptor data reported by all 3 radiologists (for the first radiologist, the leave-one-out method was used). The computer output consisted of the best calcification distribution descriptor and the best 2 calcification morphology descriptors. The results of the comparison with the data from each radiologist, respectively, were: for calcification distribution, percent agreement, 74%, 66%, and 73%, kappa value, 0.44, 0.36, and 0.46; for calcification morphology, percent agreement, 83%, 77%, and 57%, kappa value, 0.78, 0.70, and 0.44. These results indicate that the proposed computer technique can select BI-RADS descriptors in good agreement with radiologists.

Real-time, resource-constrained object classification on a micro-air vehicle

NASA Astrophysics Data System (ADS)

Buck, Louis; Ray, Laura

2013-12-01

A real-time embedded object classification algorithm is developed through the novel combination of binary feature descriptors, a bag-of-visual-words object model and the cortico-striatal loop (CSL) learning algorithm. The BRIEF, ORB and FREAK binary descriptors are tested and compared to SIFT descriptors with regard to their respective classification accuracies, execution times, and memory requirements when used with CSL on a 12.6 g ARM Cortex embedded processor running at 800 MHz. Additionally, the effect of x2 feature mapping and opponent-color representations used with these descriptors is examined. These tests are performed on four data sets of varying sizes and difficulty, and the BRIEF descriptor is found to yield the best combination of speed and classification accuracy. Its use with CSL achieves accuracies between 67% and 95% of those achieved with SIFT descriptors and allows for the embedded classification of a 128x192 pixel image in 0.15 seconds, 60 times faster than classification with SIFT. X2 mapping is found to provide substantial improvements in classification accuracy for all of the descriptors at little cost, while opponent-color descriptors are offer accuracy improvements only on colorful datasets.

Local intensity area descriptor for facial recognition in ideal and noise conditions

NASA Astrophysics Data System (ADS)

Tran, Chi-Kien; Tseng, Chin-Dar; Chao, Pei-Ju; Ting, Hui-Min; Chang, Liyun; Huang, Yu-Jie; Lee, Tsair-Fwu

2017-03-01

We propose a local texture descriptor, local intensity area descriptor (LIAD), which is applied for human facial recognition in ideal and noisy conditions. Each facial image is divided into small regions from which LIAD histograms are extracted and concatenated into a single feature vector to represent the facial image. The recognition is performed using a nearest neighbor classifier with histogram intersection and chi-square statistics as dissimilarity measures. Experiments were conducted with LIAD using the ORL database of faces (Olivetti Research Laboratory, Cambridge), the Face94 face database, the Georgia Tech face database, and the FERET database. The results demonstrated the improvement in accuracy of our proposed descriptor compared to conventional descriptors [local binary pattern (LBP), uniform LBP, local ternary pattern, histogram of oriented gradients, and local directional pattern]. Moreover, the proposed descriptor was less sensitive to noise and had low histogram dimensionality. Thus, it is expected to be a powerful texture descriptor that can be used for various computer vision problems.

A 3D model retrieval approach based on Bayesian networks lightfield descriptor

NASA Astrophysics Data System (ADS)

Xiao, Qinhan; Li, Yanjun

2009-12-01

A new 3D model retrieval methodology is proposed by exploiting a novel Bayesian networks lightfield descriptor (BNLD). There are two key novelties in our approach: (1) a BN-based method for building lightfield descriptor; and (2) a 3D model retrieval scheme based on the proposed BNLD. To overcome the disadvantages of the existing 3D model retrieval methods, we explore BN for building a new lightfield descriptor. Firstly, 3D model is put into lightfield, about 300 binary-views can be obtained along a sphere, then Fourier descriptors and Zernike moments descriptors can be calculated out from binaryviews. Then shape feature sequence would be learned into a BN model based on BN learning algorithm; Secondly, we propose a new 3D model retrieval method by calculating Kullback-Leibler Divergence (KLD) between BNLDs. Beneficial from the statistical learning, our BNLD is noise robustness as compared to the existing methods. The comparison between our method and the lightfield descriptor-based approach is conducted to demonstrate the effectiveness of our proposed methodology.

A MSFD complementary approach for the assessment of pressures, knowledge and data gaps in Southern European Seas: The PERSEUS experience.

PubMed

Crise, A; Kaberi, H; Ruiz, J; Zatsepin, A; Arashkevich, E; Giani, M; Karageorgis, A P; Prieto, L; Pantazi, M; Gonzalez-Fernandez, D; Ribera d'Alcalà, M; Tornero, V; Vassilopoulou, V; Durrieu de Madron, X; Guieu, C; Puig, P; Zenetos, A; Andral, B; Angel, D; Altukhov, D; Ayata, S D; Aktan, Y; Balcıoğlu, E; Benedetti, F; Bouchoucha, M; Buia, M-C; Cadiou, J-F; Canals, M; Chakroun, M; Christou, E; Christidis, M G; Civitarese, G; Coatu, V; Corsini-Foka, M; Cozzi, S; Deidun, A; Dell'Aquila, A; Dogrammatzi, A; Dumitrache, C; Edelist, D; Ettahiri, O; Fonda-Umani, S; Gana, S; Galgani, F; Gasparini, S; Giannakourou, A; Gomoiu, M-T; Gubanova, A; Gücü, A-C; Gürses, Ö; Hanke, G; Hatzianestis, I; Herut, B; Hone, R; Huertas, E; Irisson, J-O; İşinibilir, M; Jimenez, J A; Kalogirou, S; Kapiris, K; Karamfilov, V; Kavadas, S; Keskin, Ç; Kideyş, A E; Kocak, M; Kondylatos, G; Kontogiannis, C; Kosyan, R; Koubbi, P; Kušpilić, G; La Ferla, R; Langone, L; Laroche, S; Lazar, L; Lefkaditou, E; Lemeshko, I E; Machias, A; Malej, A; Mazzocchi, M-G; Medinets, V; Mihalopoulos, N; Miserocchi, S; Moncheva, S; Mukhanov, V; Oaie, G; Oros, A; Öztürk, A A; Öztürk, B; Panayotova, M; Prospathopoulos, A; Radu, G; Raykov, V; Reglero, P; Reygondeau, G; Rougeron, N; Salihoglu, B; Sanchez-Vidal, A; Sannino, G; Santinelli, C; Secrieru, D; Shapiro, G; Simboura, N; Shiganova, T; Sprovieri, M; Stefanova, K; Streftaris, N; Tirelli, V; Tom, M; Topaloğlu, B; Topçu, N E; Tsagarakis, K; Tsangaris, C; Tserpes, G; Tuğrul, S; Uysal, Z; Vasile, D; Violaki, K; Xu, J; Yüksek, A; Papathanassiou, E

2015-06-15

PERSEUS project aims to identify the most relevant pressures exerted on the ecosystems of the Southern European Seas (SES), highlighting knowledge and data gaps that endanger the achievement of SES Good Environmental Status (GES) as mandated by the Marine Strategy Framework Directive (MSFD). A complementary approach has been adopted, by a meta-analysis of existing literature on pressure/impact/knowledge gaps summarized in tables related to the MSFD descriptors, discriminating open waters from coastal areas. A comparative assessment of the Initial Assessments (IAs) for five SES countries has been also independently performed. The comparison between meta-analysis results and IAs shows similarities for coastal areas only. Major knowledge gaps have been detected for the biodiversity, marine food web, marine litter and underwater noise descriptors. The meta-analysis also allowed the identification of additional research themes targeting research topics that are requested to the achievement of GES. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Covariance descriptor fusion for target detection

NASA Astrophysics Data System (ADS)

Cukur, Huseyin; Binol, Hamidullah; Bal, Abdullah; Yavuz, Fatih

2016-05-01

Target detection is one of the most important topics for military or civilian applications. In order to address such detection tasks, hyperspectral imaging sensors provide useful images data containing both spatial and spectral information. Target detection has various challenging scenarios for hyperspectral images. To overcome these challenges, covariance descriptor presents many advantages. Detection capability of the conventional covariance descriptor technique can be improved by fusion methods. In this paper, hyperspectral bands are clustered according to inter-bands correlation. Target detection is then realized by fusion of covariance descriptor results based on the band clusters. The proposed combination technique is denoted Covariance Descriptor Fusion (CDF). The efficiency of the CDF is evaluated by applying to hyperspectral imagery to detect man-made objects. The obtained results show that the CDF presents better performance than the conventional covariance descriptor.

A general procedure to generate models for urban environmental-noise pollution using feature selection and machine learning methods.

PubMed

Torija, Antonio J; Ruiz, Diego P

2015-02-01

The prediction of environmental noise in urban environments requires the solution of a complex and non-linear problem, since there are complex relationships among the multitude of variables involved in the characterization and modelling of environmental noise and environmental-noise magnitudes. Moreover, the inclusion of the great spatial heterogeneity characteristic of urban environments seems to be essential in order to achieve an accurate environmental-noise prediction in cities. This problem is addressed in this paper, where a procedure based on feature-selection techniques and machine-learning regression methods is proposed and applied to this environmental problem. Three machine-learning regression methods, which are considered very robust in solving non-linear problems, are used to estimate the energy-equivalent sound-pressure level descriptor (LAeq). These three methods are: (i) multilayer perceptron (MLP), (ii) sequential minimal optimisation (SMO), and (iii) Gaussian processes for regression (GPR). In addition, because of the high number of input variables involved in environmental-noise modelling and estimation in urban environments, which make LAeq prediction models quite complex and costly in terms of time and resources for application to real situations, three different techniques are used to approach feature selection or data reduction. The feature-selection techniques used are: (i) correlation-based feature-subset selection (CFS), (ii) wrapper for feature-subset selection (WFS), and the data reduction technique is principal-component analysis (PCA). The subsequent analysis leads to a proposal of different schemes, depending on the needs regarding data collection and accuracy. The use of WFS as the feature-selection technique with the implementation of SMO or GPR as regression algorithm provides the best LAeq estimation (R(2)=0.94 and mean absolute error (MAE)=1.14-1.16 dB(A)). Copyright © 2014 Elsevier B.V. All rights reserved.

Augmented Topological Descriptors of Pore Networks for Material Science.

PubMed

Ushizima, D; Morozov, D; Weber, G H; Bianchi, A G C; Sethian, J A; Bethel, E W

2012-12-01

One potential solution to reduce the concentration of carbon dioxide in the atmosphere is the geologic storage of captured CO2 in underground rock formations, also known as carbon sequestration. There is ongoing research to guarantee that this process is both efficient and safe. We describe tools that provide measurements of media porosity, and permeability estimates, including visualization of pore structures. Existing standard algorithms make limited use of geometric information in calculating permeability of complex microstructures. This quantity is important for the analysis of biomineralization, a subsurface process that can affect physical properties of porous media. This paper introduces geometric and topological descriptors that enhance the estimation of material permeability. Our analysis framework includes the processing of experimental data, segmentation, and feature extraction and making novel use of multiscale topological analysis to quantify maximum flow through porous networks. We illustrate our results using synchrotron-based X-ray computed microtomography of glass beads during biomineralization. We also benchmark the proposed algorithms using simulated data sets modeling jammed packed bead beds of a monodispersive material.

Development of an online, publicly accessible naive Bayesian decision support tool for mammographic mass lesions based on the American College of Radiology (ACR) BI-RADS lexicon.

PubMed

Benndorf, Matthias; Kotter, Elmar; Langer, Mathias; Herda, Christoph; Wu, Yirong; Burnside, Elizabeth S

2015-06-01

To develop and validate a decision support tool for mammographic mass lesions based on a standardized descriptor terminology (BI-RADS lexicon) to reduce variability of practice. We used separate training data (1,276 lesions, 138 malignant) and validation data (1,177 lesions, 175 malignant). We created naïve Bayes (NB) classifiers from the training data with tenfold cross-validation. Our "inclusive model" comprised BI-RADS categories, BI-RADS descriptors, and age as predictive variables; our "descriptor model" comprised BI-RADS descriptors and age. The resulting NB classifiers were applied to the validation data. We evaluated and compared classifier performance with ROC-analysis. In the training data, the inclusive model yields an AUC of 0.959; the descriptor model yields an AUC of 0.910 (P < 0.001). The inclusive model is superior to the clinical performance (BI-RADS categories alone, P < 0.001); the descriptor model performs similarly. When applied to the validation data, the inclusive model yields an AUC of 0.935; the descriptor model yields an AUC of 0.876 (P < 0.001). Again, the inclusive model is superior to the clinical performance (P < 0.001); the descriptor model performs similarly. We consider our classifier a step towards a more uniform interpretation of combinations of BI-RADS descriptors. We provide our classifier at www.ebm-radiology.com/nbmm/index.html . • We provide a decision support tool for mammographic masses at www.ebm-radiology.com/nbmm/index.html . • Our tool may reduce variability of practice in BI-RADS category assignment. • A formal analysis of BI-RADS descriptors may enhance radiologists' diagnostic performance.

Descriptions and identifications of strangers by youth and adult eyewitnesses.

PubMed

Pozzulo, Joanna D; Warren, Kelly L

2003-04-01

Two studies varying target gender and mode of target exposure were conducted to compare the quantity, nature, and accuracy of free recall person descriptions provided by youths and adults. In addition, the relation among age, identification accuracy, and number of descriptors reported was considered. Youths (10-14 years) reported fewer descriptors than adults. Exterior facial descriptors (e.g., hair items) were predominant and accurately reported by youths and adults. Accuracy was consistently problematic for youths when reporting body descriptors (e.g., height, weight) and interior facial features. Youths reported a similar number of descriptors when making accurate versus inaccurate identification decisions. This pattern also was consistent for adults. With target-absent lineups, the difference in the number of descriptors reported between adults and youths was greater when making a false positive versus correct rejection.

Human region segmentation and description methods for domiciliary healthcare monitoring using chromatic methodology

NASA Astrophysics Data System (ADS)

Al-Temeemy, Ali A.

2018-03-01

A descriptor is proposed for use in domiciliary healthcare monitoring systems. The descriptor is produced from chromatic methodology to extract robust features from the monitoring system's images. It has superior discrimination capabilities, is robust to events that normally disturb monitoring systems, and requires less computational time and storage space to achieve recognition. A method of human region segmentation is also used with this descriptor. The performance of the proposed descriptor was evaluated using experimental data sets, obtained through a series of experiments performed in the Centre for Intelligent Monitoring Systems, University of Liverpool. The evaluation results show high recognition performance for the proposed descriptor in comparison to traditional descriptors, such as moments invariant. The results also show the effectiveness of the proposed segmentation method regarding distortion effects associated with domiciliary healthcare systems.

The contribution of the hydrogen bond acidity on the lipophilicity of drugs estimated from chromatographic measurements.

PubMed

Pallicer, Juan M; Pascual, Rosalia; Port, Adriana; Rosés, Martí; Ràfols, Clara; Bosch, Elisabeth

2013-02-14

The influence of the hydrogen bond acidity when the 1-octanol/water partition coefficient (log P(o/w)) of drugs is determined from chromatographic measurements was studied in this work. This influence was firstly evaluated by means of the comparison between the Abraham solvation parameter model when it is applied to express the 1-octanol/water partitioning and the chromatographic retention, expressed as the solute polarity p. Then, several hydrogen bond acidity descriptors were compared in order to determine properly the log P(o/w) of drugs. These descriptors were obtained from different software and comprise two-dimensional parameters such as the calculated Abraham hydrogen bond acidity A and three-dimensional descriptors like HDCA-2 from CODESSA program or WO1 and DRDODO descriptors calculated from Volsurf+software. The additional HOMO-LUMO polarizability descriptor should be added when the three-dimensional descriptors are used to complement the chromatographic retention. The models generated using these descriptors were compared studying the correlations between the determined log P(o/w) values and the reference ones. The comparison showed that there was no significant difference between the tested models and any of them was able to determine the log P(o/w) of drugs from a single chromatographic measurement and the correspondent molecular descriptors terms. However, the model that involved the calculated A descriptor was simpler and it is thus recommended for practical uses. Copyright © 2012 Elsevier B.V. All rights reserved.

Mapping the environmental and biogeographic complexity of the Amazon basin using remote sensing methods

NASA Astrophysics Data System (ADS)

Streher, A. S.; Cordeiro, C. L. O.; Silva, T. S. F.

2017-12-01

Mapping environmental envelopes onto geographical space has been classically important for understanding biogeographical patterns. Knowing the biotic and abiotic limits defining these envelopes, we can better understand the requirements limiting species distributions. Most present efforts in this regard have focused on single-species distribution models, but the current breadth and accessibility of quantitative, spatially explicit environmental information can also be explored from an environment-first perspective. We thus used remote sensing to determine the occurrence of environmental discontinuities in the Amazon region and evaluated if such discontinuities may act as barriers to determine species distribution and range limits, forming clear environmental envelopes. We combined data on topography (SRTM), precipitation (CHIRPS), vegetation descriptors (PALSAR-1 backscattering, biomass, NDVI) and temperature (MODIS), using object-based image analysis and unsupervised learning to map environmental envelopes. We identified 14 environmental envelopes for the Amazon sensu latissimo region, mainly delimited by changes in vegetation, topography and precipitation. The resulting envelopes were compared to the distribution of 120 species of Trogonidae, Galbulidae, Bucconidae, Cebidae, Hylidae and Lecythidaceae, amounting to 22,649 occurrence records within the Amazonregion. We determined species prevalence in each envelope by calculating the ratio between species relative frequency per envelope and envelope relative frequency (area) in the complete map. Values closer to 1 indicate a high degree of prevalence. We found strong envelope associations (prevalence > 0.5) for 20 species (17% of analyzed taxa). Although several biogeographical and ecological factors will influence the distribution of a species, our results show that not only geographical barriers, but also modern environmental discontinuities may limit the distribution of some species., and may have also done so in the past. Our work also highlights the environmental complexity of the Amazon region, often considered as "environmentally homogeneous", and shows how environmental mapping can contribute to better understanding of the processes explaining the current assembly and distribution of Amazon biodiversity.

A novel binary shape context for 3D local surface description

NASA Astrophysics Data System (ADS)

Dong, Zhen; Yang, Bisheng; Liu, Yuan; Liang, Fuxun; Li, Bijun; Zang, Yufu

2017-08-01

3D local surface description is now at the core of many computer vision technologies, such as 3D object recognition, intelligent driving, and 3D model reconstruction. However, most of the existing 3D feature descriptors still suffer from low descriptiveness, weak robustness, and inefficiency in both time and memory. To overcome these challenges, this paper presents a robust and descriptive 3D Binary Shape Context (BSC) descriptor with high efficiency in both time and memory. First, a novel BSC descriptor is generated for 3D local surface description, and the performance of the BSC descriptor under different settings of its parameters is analyzed. Next, the descriptiveness, robustness, and efficiency in both time and memory of the BSC descriptor are evaluated and compared to those of several state-of-the-art 3D feature descriptors. Finally, the performance of the BSC descriptor for 3D object recognition is also evaluated on a number of popular benchmark datasets, and an urban-scene dataset is collected by a terrestrial laser scanner system. Comprehensive experiments demonstrate that the proposed BSC descriptor obtained high descriptiveness, strong robustness, and high efficiency in both time and memory and achieved high recognition rates of 94.8%, 94.1% and 82.1% on the considered UWA, Queen, and WHU datasets, respectively.

Renal Function Descriptors in Neonates: Which Creatinine-Based Formula Best Describes Vancomycin Clearance?

PubMed

Bhongsatiern, Jiraganya; Stockmann, Chris; Yu, Tian; Constance, Jonathan E; Moorthy, Ganesh; Spigarelli, Michael G; Desai, Pankaj B; Sherwin, Catherine M T

2016-05-01

Growth and maturational changes have been identified as significant covariates in describing variability in clearance of renally excreted drugs such as vancomycin. Because of immaturity of clearance mechanisms, quantification of renal function in neonates is of importance. Several serum creatinine (SCr)-based renal function descriptors have been developed in adults and children, but none are selectively derived for neonates. This review summarizes development of the neonatal kidney and discusses assessment of the renal function regarding estimation of glomerular filtration rate using renal function descriptors. Furthermore, identification of the renal function descriptors that best describe the variability of vancomycin clearance was performed in a sample study of a septic neonatal cohort. Population pharmacokinetic models were developed applying a combination of age-weight, renal function descriptors, or SCr alone. In addition to age and weight, SCr or renal function descriptors significantly reduced variability of vancomycin clearance. The population pharmacokinetic models with Léger and modified Schwartz formulas were selected as the optimal final models, although the other renal function descriptors and SCr provided reasonably good fit to the data, suggesting further evaluation of the final models using external data sets and cross validation. The present study supports incorporation of renal function descriptors in the estimation of vancomycin clearance in neonates. © 2015, The American College of Clinical Pharmacology.

Robust image region descriptor using local derivative ordinal binary pattern

NASA Astrophysics Data System (ADS)

Shang, Jun; Chen, Chuanbo; Pei, Xiaobing; Liang, Hu; Tang, He; Sarem, Mudar

2015-05-01

Binary image descriptors have received a lot of attention in recent years, since they provide numerous advantages, such as low memory footprint and efficient matching strategy. However, they utilize intermediate representations and are generally less discriminative than floating-point descriptors. We propose an image region descriptor, namely local derivative ordinal binary pattern, for object recognition and image categorization. In order to preserve more local contrast and edge information, we quantize the intensity differences between the central pixels and their neighbors of the detected local affine covariant regions in an adaptive way. These differences are then sorted and mapped into binary codes and histogrammed with a weight of the sum of the absolute value of the differences. Furthermore, the gray level of the central pixel is quantized to further improve the discriminative ability. Finally, we combine them to form a joint histogram to represent the features of the image. We observe that our descriptor preserves more local brightness and edge information than traditional binary descriptors. Also, our descriptor is robust to rotation, illumination variations, and other geometric transformations. We conduct extensive experiments on the standard ETHZ and Kentucky datasets for object recognition and PASCAL for image classification. The experimental results show that our descriptor outperforms existing state-of-the-art methods.

PyBioMed: a python library for various molecular representations of chemicals, proteins and DNAs and their interactions.

PubMed

Dong, Jie; Yao, Zhi-Jiang; Zhang, Lin; Luo, Feijun; Lin, Qinlu; Lu, Ai-Ping; Chen, Alex F; Cao, Dong-Sheng

2018-03-20

With the increasing development of biotechnology and informatics technology, publicly available data in chemistry and biology are undergoing explosive growth. Such wealthy information in these data needs to be extracted and transformed to useful knowledge by various data mining methods. Considering the amazing rate at which data are accumulated in chemistry and biology fields, new tools that process and interpret large and complex interaction data are increasingly important. So far, there are no suitable toolkits that can effectively link the chemical and biological space in view of molecular representation. To further explore these complex data, an integrated toolkit for various molecular representation is urgently needed which could be easily integrated with data mining algorithms to start a full data analysis pipeline. Herein, the python library PyBioMed is presented, which comprises functionalities for online download for various molecular objects by providing different IDs, the pretreatment of molecular structures, the computation of various molecular descriptors for chemicals, proteins, DNAs and their interactions. PyBioMed is a feature-rich and highly customized python library used for the characterization of various complex chemical and biological molecules and interaction samples. The current version of PyBioMed could calculate 775 chemical descriptors and 19 kinds of chemical fingerprints, 9920 protein descriptors based on protein sequences, more than 6000 DNA descriptors from nucleotide sequences, and interaction descriptors from pairwise samples using three different combining strategies. Several examples and five real-life applications were provided to clearly guide the users how to use PyBioMed as an integral part of data analysis projects. By using PyBioMed, users are able to start a full pipelining from getting molecular data, pretreating molecules, molecular representation to constructing machine learning models conveniently. PyBioMed provides various user-friendly and highly customized APIs to calculate various features of biological molecules and complex interaction samples conveniently, which aims at building integrated analysis pipelines from data acquisition, data checking, and descriptor calculation to modeling. PyBioMed is freely available at http://projects.scbdd.com/pybiomed.html .

Global chemical reactivity parameters for several chiral beta-blockers from the Density Functional Theory viewpoint

PubMed Central

TALMACIU, MONA MARIA; BODOKI, EDE; OPREAN, RADU

2016-01-01

Background and aim Beta-adrenergic antagonists have been established as first line treatment in the medical management of hypertension, acute coronary syndrome and other cardiovascular diseases, as well as for the prevention of initial episodes of gastrointestinal bleeding in patients with cirrhosis and esophageal varices, glaucoma, and have recently become the main form of treatment of infantile hemangiomas. The aim of the present study is to calculate for 14 beta-blockers several quantum chemical descriptors in order to interpret various molecular properties such as electronic structure, conformation, reactivity, in the interest of determining how such descriptors could have an impact on our understanding of the experimental observations and describing various aspects of chemical binding of beta-blockers in terms of these descriptors. Methods The 2D chemical structures of the beta-blockers (14 molecules with one stereogenic center) were cleaned in 3D, their geometry was preoptimized using the software MOPAC2012, by PM6 method, and then further refined using standard settings in MOE; HOMO and LUMO descriptors were calculated using semi-empirical molecular orbital methods AM1, MNDO and PM3, for the lowest energy conformers and the quantum chemical descriptors (HLG, electronegativity, chemical potential, hardness and softness, electrophilicity) were then calculated. Results According to HOMO-LUMO gap and the chemical hardness the most stable compounds are alprenolol, bisoprolol and esmolol. The softness values calculated for the study molecules revolve around 0.100. Propranolol, sotalol and timolol have among the highest electrophilicity index of the studied beta-blocker molecules. Results obtained from calculations showed that acebutolol, atenolol, timolol and sotalol have the highest values for the electronegativity index. Conclusions The future aim is to determine whether it is possible to find a valid correlation between these descriptors and the physicochemical behavior of the molecules from this class. The HLG could be correlated to the experimentally recorded electrochemical properties of the molecules. HOMO could be correlated to the observed oxidation potential, since the required voltage is related to the energy of the HOMO, because only the electron from this orbital is involved in the oxidation process. PMID:27857521

Completion processing for data communications instructions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blocksome, Michael A; Kumar, Sameer; Parker, Jeffrey J

Completion processing of data communications instructions in a distributed computing environment, including receiving, in an active messaging interface (`AMI`) data communications instructions, at least one instruction specifying a callback function; injecting into an injection FIFO buffer of a data communication adapter, an injection descriptor, each slot in the injection FIFO buffer having a corresponding slot in a pending callback list; listing in the pending callback list any callback function specified by an instruction, incrementing a pending callback counter for each listed callback function; transferring payload data as per each injection descriptor, incrementing a transfer counter upon completion of each transfer;more » determining from counter values whether the pending callback list presently includes callback functions whose data transfers have been completed; calling by the AMI any such callback functions from the pending callback list, decrementing the pending callback counter for each callback function called.« less

A comparison of two independent measurements and analysis of jet aircraft flyover noise

NASA Technical Reports Server (NTRS)

Hosier, R. N.

1977-01-01

Flyover noise measurements were made simultaneously by two groups. The measurements were made close to one another for the same flyover conditions and with similar measurement procedures, but with different acoustic equipment and personnel. Each group also independently processed the data in accordance with FAR 36 procedures, indluding corrections to reference meteorological, performance, and flight-path conditions. Measured and corrected data, from 24 controlled flyovers processed by both groups, are compared and the differences in the results obtained by the two groups are discussed. It is observed that the average value of the difference between the groups' measured acoustic descriptors (PNL, PNLTM, and EPNL) was less than or = 0.8 db; the average difference for the corrected descriptors (PNL, PNLTM, and EPNL) was less than or = 1.5 db. Causes of the differences were found to be mainly related to different spectrum extrapolation and preemphasis techniques used by the two groups.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cuevas, F.A.; Curilef, S., E-mail: scurilef@ucn.cl; Plastino, A.R., E-mail: arplastino@ugr.es

The spread of a wave-packet (or its deformation) is a very important topic in quantum mechanics. Understanding this phenomenon is relevant in connection with the study of diverse physical systems. In this paper we apply various 'spreading measures' to characterize the evolution of an initially localized wave-packet in a tight-binding lattice, with special emphasis on information-theoretical measures. We investigate the behavior of both the probability distribution associated with the wave packet and the concomitant probability current. Complexity measures based upon Renyi entropies appear to be particularly good descriptors of the details of the delocalization process. - Highlights: > Spread ofmore » highly localized wave-packet in the tight-binding lattice. > Entropic and information-theoretical characterization is used to understand the delocalization. > The behavior of both the probability distribution and the concomitant probability current is investigated. > Renyi entropies appear to be good descriptors of the details of the delocalization process.« less

Analysis of Stomata Distribution Patterns for Quantification of the Foliar Plasticity of Tradescantia Zebrina

NASA Astrophysics Data System (ADS)

Batista Florindo, Joao; Landini, Gabriel; Almeida Filho, Humberto; Martinez Bruno, Odemir

2015-09-01

Here we propose a method for the analysis of the stomata distribution patterns on the surface of plant leaves. We also investigate how light exposure during growth can affect stomata distribution and the plasticity of leaves. Understanding foliar plasticity (the ability of leaves to modify their structural organization to adapt to changing environmental resources) is a fundamental problem in Agricultural and Environmental Sciences. Most published work on quantification of stomata has concentrated on descriptions of their density per unit of leaf area, however density alone does not provide a complete description of the problem and leaves several unanswered questions (e.g. whether the stomata patterns change across various areas of the leaf, or how the patterns change under varying observational scales). We used two approaches here, to know, multiscale fractal dimension and complex networks, as a means to provide a description of the complexity of these distributions. In the experiments, we used 18 samples from the plant Tradescantia Zebrina grown under three different conditions (4 hours of artificial light each day, 24 hours of artificial light each day, and sunlight) for a total of 69 days. The network descriptors were capable of correctly discriminating the different conditions in 88% of cases, while the fractal descriptors discriminated 83% of the samples. This is a significant improvement over the correct classification rates achieved when using only stomata density (56% of the samples).

Circular blurred shape model for multiclass symbol recognition.

PubMed

Escalera, Sergio; Fornés, Alicia; Pujol, Oriol; Lladós, Josep; Radeva, Petia

2011-04-01

In this paper, we propose a circular blurred shape model descriptor to deal with the problem of symbol detection and classification as a particular case of object recognition. The feature extraction is performed by capturing the spatial arrangement of significant object characteristics in a correlogram structure. The shape information from objects is shared among correlogram regions, where a prior blurring degree defines the level of distortion allowed in the symbol, making the descriptor tolerant to irregular deformations. Moreover, the descriptor is rotation invariant by definition. We validate the effectiveness of the proposed descriptor in both the multiclass symbol recognition and symbol detection domains. In order to perform the symbol detection, the descriptors are learned using a cascade of classifiers. In the case of multiclass categorization, the new feature space is learned using a set of binary classifiers which are embedded in an error-correcting output code design. The results over four symbol data sets show the significant improvements of the proposed descriptor compared to the state-of-the-art descriptors. In particular, the results are even more significant in those cases where the symbols suffer from elastic deformations.

Assessing the statistical relationships among water-derived climate variables, rainfall, and remotely sensed features of vegetation: implications for evaluating the habitat of ticks.

PubMed

Alonso-Carné, J; García-Martín, A; Estrada-Peña, A

2015-01-01

Ticks are sensitive to changes in relative humidity and saturation deficit at the microclimate scale. Trends and changes in rainfall are commonly used as descriptors of field observations of tick populations, to capture the climate niche of ticks or to predict the climate suitability for ticks under future climate scenarios. We evaluated daily and monthly relationships between rainfall, relative humidity and saturation deficit over different ecosystems in Europe using daily climate values from 177 stations over a period of 10 years. We demonstrate that rainfall is poorly correlated with both relative humidity and saturation deficit in any of the ecological domains studied. We conclude that the amount of rainfall recorded in 1 day does not correlate with the values of humidity or saturation deficit recorded 24 h later: rainfall is not an adequate surrogate for evaluating the physiological processes of ticks at regional scales. We compared the Normalized Difference Vegetation Index (NDVI), a descriptor of photosynthetic activity, at a spatial resolution of 0.05°, with monthly averages of relative humidity and saturation deficit and also determined a lack of significant correlation. With the limitations of spatial scale and habitat coverage of this study, we suggest that the rainfall or NDVI cannot replace relative humidity or saturation deficit as descriptors of tick processes.

Object tracking on mobile devices using binary descriptors

NASA Astrophysics Data System (ADS)

Savakis, Andreas; Quraishi, Mohammad Faiz; Minnehan, Breton

2015-03-01

With the growing ubiquity of mobile devices, advanced applications are relying on computer vision techniques to provide novel experiences for users. Currently, few tracking approaches take into consideration the resource constraints on mobile devices. Designing efficient tracking algorithms and optimizing performance for mobile devices can result in better and more efficient tracking for applications, such as augmented reality. In this paper, we use binary descriptors, including Fast Retina Keypoint (FREAK), Oriented FAST and Rotated BRIEF (ORB), Binary Robust Independent Features (BRIEF), and Binary Robust Invariant Scalable Keypoints (BRISK) to obtain real time tracking performance on mobile devices. We consider both Google's Android and Apple's iOS operating systems to implement our tracking approach. The Android implementation is done using Android's Native Development Kit (NDK), which gives the performance benefits of using native code as well as access to legacy libraries. The iOS implementation was created using both the native Objective-C and the C++ programing languages. We also introduce simplified versions of the BRIEF and BRISK descriptors that improve processing speed without compromising tracking accuracy.

The implementation of contour-based object orientation estimation algorithm in FPGA-based on-board vision system

NASA Astrophysics Data System (ADS)

Alpatov, Boris; Babayan, Pavel; Ershov, Maksim; Strotov, Valery

2016-10-01

This paper describes the implementation of the orientation estimation algorithm in FPGA-based vision system. An approach to estimate an orientation of objects lacking axial symmetry is proposed. Suggested algorithm is intended to estimate orientation of a specific known 3D object based on object 3D model. The proposed orientation estimation algorithm consists of two stages: learning and estimation. Learning stage is devoted to the exploring of studied object. Using 3D model we can gather set of training images by capturing 3D model from viewpoints evenly distributed on a sphere. Sphere points distribution is made by the geosphere principle. Gathered training image set is used for calculating descriptors, which will be used in the estimation stage of the algorithm. The estimation stage is focusing on matching process between an observed image descriptor and the training image descriptors. The experimental research was performed using a set of images of Airbus A380. The proposed orientation estimation algorithm showed good accuracy in all case studies. The real-time performance of the algorithm in FPGA-based vision system was demonstrated.

Contour-based object orientation estimation

NASA Astrophysics Data System (ADS)

Alpatov, Boris; Babayan, Pavel

2016-04-01

Real-time object orientation estimation is an actual problem of computer vision nowadays. In this paper we propose an approach to estimate an orientation of objects lacking axial symmetry. Proposed algorithm is intended to estimate orientation of a specific known 3D object, so 3D model is required for learning. The proposed orientation estimation algorithm consists of 2 stages: learning and estimation. Learning stage is devoted to the exploring of studied object. Using 3D model we can gather set of training images by capturing 3D model from viewpoints evenly distributed on a sphere. Sphere points distribution is made by the geosphere principle. It minimizes the training image set. Gathered training image set is used for calculating descriptors, which will be used in the estimation stage of the algorithm. The estimation stage is focusing on matching process between an observed image descriptor and the training image descriptors. The experimental research was performed using a set of images of Airbus A380. The proposed orientation estimation algorithm showed good accuracy (mean error value less than 6°) in all case studies. The real-time performance of the algorithm was also demonstrated.

Graphic matching based on shape contexts and reweighted random walks

NASA Astrophysics Data System (ADS)

Zhang, Mingxuan; Niu, Dongmei; Zhao, Xiuyang; Liu, Mingjun

2018-04-01

Graphic matching is a very critical issue in all aspects of computer vision. In this paper, a new graphics matching algorithm combining shape contexts and reweighted random walks was proposed. On the basis of the local descriptor, shape contexts, the reweighted random walks algorithm was modified to possess stronger robustness and correctness in the final result. Our main process is to use the descriptor of the shape contexts for the random walk on the iteration, of which purpose is to control the random walk probability matrix. We calculate bias matrix by using descriptors and then in the iteration we use it to enhance random walks' and random jumps' accuracy, finally we get the one-to-one registration result by discretization of the matrix. The algorithm not only preserves the noise robustness of reweighted random walks but also possesses the rotation, translation, scale invariance of shape contexts. Through extensive experiments, based on real images and random synthetic point sets, and comparisons with other algorithms, it is confirmed that this new method can produce excellent results in graphic matching.

New descriptor for skeletons of planar shapes: the calypter

NASA Astrophysics Data System (ADS)

Pirard, Eric; Nivart, Jean-Francois

1994-05-01

The mathematical definition of the skeleton as the locus of centers of maximal inscribed discs is a nondigitizable one. The idea presented in this paper is to incorporate the skeleton information and the chain-code of the contour into a single descriptor by associating to each point of a contour the center and radius of the maximum inscribed disc tangent at that point. This new descriptor is called calypter. The encoding of a calypter is a three stage algorithm: (1) chain coding of the contour; (2) euclidean distance transformation, (3) climbing on the distance relief from each point of the contour towards the corresponding maximal inscribed disc center. Here we introduce an integer euclidean distance transform called the holodisc distance transform. The major interest of this holodisc transform is to confer 8-connexity to the isolevels of the generated distance relief thereby allowing a climbing algorithm to proceed step by step towards the centers of the maximal inscribed discs. The calypter has a cyclic structure delivering high speed access to the skeleton data. Its potential uses are in high speed euclidean mathematical morphology, shape processing, and analysis.

Electronic forces as descriptors of nucleophilic and electrophilic regioselectivity and stereoselectivity.

PubMed

Liu, Shubin; Rong, Chunying; Lu, Tian

2017-01-04

One of the main tasks of theoretical chemistry is to rationalize computational results with chemical insights. Key concepts of such nature include nucleophilicity, electrophilicity, regioselectivity, and stereoselectivity. While computational tools are available to predict barrier heights and other reactivity properties with acceptable accuracy, a conceptual framework to appreciate above quantities is still lacking. In this work, we introduce the electronic force as the fundamental driving force of chemical processes to understand and predict molecular reactivity. It has three components but only two are independent. These forces, electrostatic and steric, can be employed as reliable descriptors for nucleophilic and electrophilic regioselectivity and stereoselectivity. The advantages of using these forces to evaluate molecular reactivity are that electrophilic and nucleophilic attacks are featured by distinct characteristics in the electrostatic force and no knowledge of quantum effects included in the kinetic and exchange-correlation energies is required. Examples are provided to highlight the validity and general applicability of these reactivity descriptors. Possible applications in ambident reactivity, σ and π holes, frustrated Lewis pairs, and stereoselective reactions are also included in this work.

a Clustering-Based Approach for Evaluation of EO Image Indexing

NASA Astrophysics Data System (ADS)

Bahmanyar, R.; Rigoll, G.; Datcu, M.

2013-09-01

The volume of Earth Observation data is increasing immensely in order of several Terabytes a day. Therefore, to explore and investigate the content of this huge amount of data, developing more sophisticated Content-Based Information Retrieval (CBIR) systems are highly demanded. These systems should be able to not only discover unknown structures behind the data, but also provide relevant results to the users' queries. Since in any retrieval system the images are processed based on a discrete set of their features (i.e., feature descriptors), study and assessment of the structure of feature space, build by different feature descriptors, is of high importance. In this paper, we introduce a clustering-based approach to study the content of image collections. In our approach, we claim that using both internal and external evaluation of clusters for different feature descriptors, helps to understand the structure of feature space. Moreover, the semantic understanding of users about the images also can be assessed. To validate the performance of our approach, we used an annotated Synthetic Aperture Radar (SAR) image collection. Quantitative results besides the visualization of feature space demonstrate the applicability of our approach.

Prediction and Dissection of Protein-RNA Interactions by Molecular Descriptors.

PubMed

Liu, Zhi-Ping; Chen, Luonan

2016-01-01

Protein-RNA interactions play crucial roles in numerous biological processes. However, detecting the interactions and binding sites between protein and RNA by traditional experiments is still time consuming and labor costing. Thus, it is of importance to develop bioinformatics methods for predicting protein-RNA interactions and binding sites. Accurate prediction of protein-RNA interactions and recognitions will highly benefit to decipher the interaction mechanisms between protein and RNA, as well as to improve the RNA-related protein engineering and drug design. In this work, we summarize the current bioinformatics strategies of predicting protein-RNA interactions and dissecting protein-RNA interaction mechanisms from local structure binding motifs. In particular, we focus on the feature-based machine learning methods, in which the molecular descriptors of protein and RNA are extracted and integrated as feature vectors of representing the interaction events and recognition residues. In addition, the available methods are classified and compared comprehensively. The molecular descriptors are expected to elucidate the binding mechanisms of protein-RNA interaction and reveal the functional implications from structural complementary perspective.

Spatio-temporal features for tracking and quadruped/biped discrimination

NASA Astrophysics Data System (ADS)

Rickman, Rick; Copsey, Keith; Bamber, David C.; Page, Scott F.

2012-05-01

Techniques such as SIFT and SURF facilitate efficient and robust image processing operations through the use of sparse and compact spatial feature descriptors and show much potential for defence and security applications. This paper considers the extension of such techniques to include information from the temporal domain, to improve utility in applications involving moving imagery within video data. In particular, the paper demonstrates how spatio-temporal descriptors can be used very effectively as the basis of a target tracking system and as target discriminators which can distinguish between bipeds and quadrupeds. Results using sequences of video imagery of walking humans and dogs are presented, and the relative merits of the approach are discussed.

Food product design: emerging evidence for food policy.

PubMed

Al-Hamdani, Mohammed; Smith, Steven

2017-03-01

The research on the impact of specific brand elements such as food descriptors and package colors is underexplored. We tested whether a "light" color and a "low-calorie" descriptor on food packages gain favorable consumer perception ratings as compared with regular packages. Our online experiment recruited 406 adults in a 3 (product type: Chips versus Juice versus Yoghurt) × 2 (descriptor type: regular versus low-calorie) × 2 (color type: regular versus light) mixed design. Dependent variables were sensory (evaluations of the product's nutritional value and quality), product-based (evaluations of the product's physical appeal), and consumer-based (evaluations of the potential consumers of the product) scales. "Low-calorie" descriptors were found to increase sensory ratings as compared with regular descriptors and light-colored packages received higher product-based ratings as compared with their regular-colored counterparts. Food package color and descriptors present a promising venue for understanding preventative measures against obesity.[Formula: see text].

Identifying factors of comfort in using hand tools.

PubMed

Kuijt-Evers, L F M; Groenesteijn, L; de Looze, M P; Vink, P

2004-09-01

To design comfortable hand tools, knowledge about comfort/discomfort in using hand tools is required. We investigated which factors determine comfort/discomfort in using hand tools according to users. Therefore, descriptors of comfort/discomfort in using hand tools were collected from literature and interviews. After that, the relatedness of a selection of the descriptors to comfort in using hand tools was investigated. Six comfort factors could be distinguished (functionality, posture and muscles, irritation and pain of hand and fingers, irritation of hand surface, handle characteristics, aesthetics). These six factors can be classified into three meaningful groups: functionality, physical interaction and appearance. The main conclusions were that (1) the same descriptors were related to comfort and discomfort in using hand tools, (2) descriptors of functionality are most related to comfort in using hand tools followed by descriptors of physical interaction and (3) descriptors of appearance become secondary in comfort in using hand tools.

Design of an optimal preview controller for linear discrete-time descriptor systems with state delay

NASA Astrophysics Data System (ADS)

Cao, Mengjuan; Liao, Fucheng

2015-04-01

In this paper, the linear discrete-time descriptor system with state delay is studied, and a design method for an optimal preview controller is proposed. First, by using the discrete lifting technique, the original system is transformed into a general descriptor system without state delay in form. Then, taking advantage of the first-order forward difference operator, we construct a descriptor augmented error system, including the state vectors of the lifted system, error vectors, and desired target signals. Rigorous mathematical proofs are given for the regularity, stabilisability, causal controllability, and causal observability of the descriptor augmented error system. Based on these, the optimal preview controller with preview feedforward compensation for the original system is obtained by using the standard optimal regulator theory of the descriptor system. The effectiveness of the proposed method is shown by numerical simulation.

Impact of low alcohol verbal descriptors on perceived strength: An experimental study.

PubMed

Vasiljevic, Milica; Couturier, Dominique-Laurent; Marteau, Theresa M

2018-02-01

Low alcohol labels are a set of labels that carry descriptors such as 'low' or 'lighter' to denote alcohol content in beverages. There is growing interest from policymakers and producers in lower strength alcohol products. However, there is a lack of evidence on how the general population perceives verbal descriptors of strength. The present research examines consumers' perceptions of strength (% ABV) and appeal of alcohol products using low or high alcohol verbal descriptors. A within-subjects experimental study in which participants rated the strength and appeal of 18 terms denoting low (nine terms), high (eight terms) and regular (one term) strengths for either (1) wine or (2) beer according to drinking preference. Thousand six hundred adults (796 wine and 804 beer drinkers) sampled from a nationally representative UK panel. Low, Lower, Light, Lighter, and Reduced formed a cluster and were rated as denoting lower strength products than Regular, but higher strength than the cluster with intensifiers consisting of Extra Low, Super Low, Extra Light, and Super Light. Similar clustering in perceived strength was observed amongst the high verbal descriptors. Regular was the most appealing strength descriptor, with the low and high verbal descriptors using intensifiers rated least appealing. The perceived strength and appeal of alcohol products diminished the more the verbal descriptors implied a deviation from Regular. The implications of these findings are discussed in terms of policy implications for lower strength alcohol labelling and associated public health outcomes. Statement of contribution What is already known about this subject? Current UK and EU legislation limits the number of low strength verbal descriptors and the associated alcohol by volume (ABV) to 1.2% ABV and lower. There is growing interest from policymakers and producers to extend the range of lower strength alcohol products above the current cap of 1.2% ABV set out in national legislation. There is a lack of evidence on how the general population perceives verbal descriptors of alcohol product strength (both low and high). What does this study add? Verbal descriptors of lower strength wine and beer form two clusters and effectively communicate reduced alcohol content. Low, Lower, Light, Lighter, and Reduced were considered lower in strength than Regular (average % ABV). Descriptors using intensifiers (Extra Low, Super Low, Extra Light, and Super Light) were considered lowest in strength. Similar clustering in perceived strength was observed amongst the high verbal descriptors. The appeal of alcohol products reduced the more the verbal descriptors implied a deviation from Regular. © 2017 The Authors. British Journal of Health Psychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.

On application of kernel PCA for generating stimulus features for fMRI during continuous music listening.

PubMed

Tsatsishvili, Valeri; Burunat, Iballa; Cong, Fengyu; Toiviainen, Petri; Alluri, Vinoo; Ristaniemi, Tapani

2018-06-01

There has been growing interest towards naturalistic neuroimaging experiments, which deepen our understanding of how human brain processes and integrates incoming streams of multifaceted sensory information, as commonly occurs in real world. Music is a good example of such complex continuous phenomenon. In a few recent fMRI studies examining neural correlates of music in continuous listening settings, multiple perceptual attributes of music stimulus were represented by a set of high-level features, produced as the linear combination of the acoustic descriptors computationally extracted from the stimulus audio. NEW METHOD: fMRI data from naturalistic music listening experiment were employed here. Kernel principal component analysis (KPCA) was applied to acoustic descriptors extracted from the stimulus audio to generate a set of nonlinear stimulus features. Subsequently, perceptual and neural correlates of the generated high-level features were examined. The generated features captured musical percepts that were hidden from the linear PCA features, namely Rhythmic Complexity and Event Synchronicity. Neural correlates of the new features revealed activations associated to processing of complex rhythms, including auditory, motor, and frontal areas. Results were compared with the findings in the previously published study, which analyzed the same fMRI data but applied linear PCA for generating stimulus features. To enable comparison of the results, methodology for finding stimulus-driven functional maps was adopted from the previous study. Exploiting nonlinear relationships among acoustic descriptors can lead to the novel high-level stimulus features, which can in turn reveal new brain structures involved in music processing. Copyright © 2018 Elsevier B.V. All rights reserved.

Mobile Visual Search Based on Histogram Matching and Zone Weight Learning

NASA Astrophysics Data System (ADS)

Zhu, Chuang; Tao, Li; Yang, Fan; Lu, Tao; Jia, Huizhu; Xie, Xiaodong

2018-01-01

In this paper, we propose a novel image retrieval algorithm for mobile visual search. At first, a short visual codebook is generated based on the descriptor database to represent the statistical information of the dataset. Then, an accurate local descriptor similarity score is computed by merging the tf-idf weighted histogram matching and the weighting strategy in compact descriptors for visual search (CDVS). At last, both the global descriptor matching score and the local descriptor similarity score are summed up to rerank the retrieval results according to the learned zone weights. The results show that the proposed approach outperforms the state-of-the-art image retrieval method in CDVS.

An Analysis of Descriptors of Volatile Organic Compounds and Their Impact on Rate Constant for Reaction with Hydroxyl Radicals

DTIC Science & Technology

2018-05-01

the descriptors were correlated to experimental rate constants. The five descriptors fell into one of two categories: whole molecule descriptors or...model based on these correlations . Although that goal was not achieved in full, considerable progress has been made, and there is potential for a...readme.txt) and compiled. We then searched for correlations between the calculated properties from theory and the experimental measurements of reaction rate

Learning Rotation-Invariant Local Binary Descriptor.

PubMed

Duan, Yueqi; Lu, Jiwen; Feng, Jianjiang; Zhou, Jie

2017-08-01

In this paper, we propose a rotation-invariant local binary descriptor (RI-LBD) learning method for visual recognition. Compared with hand-crafted local binary descriptors, such as local binary pattern and its variants, which require strong prior knowledge, local binary feature learning methods are more efficient and data-adaptive. Unlike existing learning-based local binary descriptors, such as compact binary face descriptor and simultaneous local binary feature learning and encoding, which are susceptible to rotations, our RI-LBD first categorizes each local patch into a rotational binary pattern (RBP), and then jointly learns the orientation for each pattern and the projection matrix to obtain RI-LBDs. As all the rotation variants of a patch belong to the same RBP, they are rotated into the same orientation and projected into the same binary descriptor. Then, we construct a codebook by a clustering method on the learned binary codes, and obtain a histogram feature for each image as the final representation. In order to exploit higher order statistical information, we extend our RI-LBD to the triple rotation-invariant co-occurrence local binary descriptor (TRICo-LBD) learning method, which learns a triple co-occurrence binary code for each local patch. Extensive experimental results on four different visual recognition tasks, including image patch matching, texture classification, face recognition, and scene classification, show that our RI-LBD and TRICo-LBD outperform most existing local descriptors.

Determination of Abraham model solute descriptors for the monomeric and dimeric forms of trans-cinnamic acid using measured solubilities from the Open Notebook Science Challenge.

PubMed

Bradley, Jean-Claude; Abraham, Michael H; Acree, William E; Lang, Andrew Sid; Beck, Samantha N; Bulger, David A; Clark, Elizabeth A; Condron, Lacey N; Costa, Stephanie T; Curtin, Evan M; Kurtu, Sozit B; Mangir, Mark I; McBride, Matthew J

2015-01-01

Calculating Abraham descriptors from solubility values requires that the solute have the same form when dissolved in all solvents. However, carboxylic acids can form dimers when dissolved in non-polar solvents. For such compounds Abraham descriptors can be calculated for both the monomeric and dimeric forms by treating the polar and non-polar systems separately. We illustrate the method of how this can be done by calculating the Abraham descriptors for both the monomeric and dimeric forms of trans-cinnamic acid, the first time that descriptors for a carboxylic acid dimer have been obtained. Abraham descriptors were calculated for the monomeric form of trans-cinnamic acid using experimental solubility measurements in polar solvents from the Open Notebook Science Challenge together with a number of water-solvent partition coefficients from the literature. Similarly, experimental solubility measurements in non-polar solvents were used to determine Abraham descriptors for the trans-cinnamic acid dimer. Abraham descriptors were calculated for both the monomeric and dimeric forms of trans-cinnamic acid. This allows for the prediction of further solubilities of trans-cinnamic acid in both polar and non-polar solvents with an error of about 0.10 log units. Graphical abstractMolar concentration of trans-cinnamic acid in various polar and non-polar solvents.

On the Relationship between Molecular Hit Rates in High-Throughput Screening and Molecular Descriptors.

PubMed

Hansson, Mari; Pemberton, John; Engkvist, Ola; Feierberg, Isabella; Brive, Lars; Jarvis, Philip; Zander-Balderud, Linda; Chen, Hongming

2014-06-01

High-throughput screening (HTS) is widely used in the pharmaceutical industry to identify novel chemical starting points for drug discovery projects. The current study focuses on the relationship between molecular hit rate in recent in-house HTS and four common molecular descriptors: lipophilicity (ClogP), size (heavy atom count, HEV), fraction of sp(3)-hybridized carbons (Fsp3), and fraction of molecular framework (f(MF)). The molecular hit rate is defined as the fraction of times the molecule has been assigned as active in the HTS campaigns where it has been screened. Beta-binomial statistical models were built to model the molecular hit rate as a function of these descriptors. The advantage of the beta-binomial statistical models is that the correlation between the descriptors is taken into account. Higher degree polynomial terms of the descriptors were also added into the beta-binomial statistic model to improve the model quality. The relative influence of different molecular descriptors on molecular hit rate has been estimated, taking into account that the descriptors are correlated to each other through applying beta-binomial statistical modeling. The results show that ClogP has the largest influence on the molecular hit rate, followed by Fsp3 and HEV. f(MF) has only a minor influence besides its correlation with the other molecular descriptors. © 2013 Society for Laboratory Automation and Screening.

Chi-square-based scoring function for categorization of MEDLINE citations.

PubMed

Kastrin, A; Peterlin, B; Hristovski, D

2010-01-01

Text categorization has been used in biomedical informatics for identifying documents containing relevant topics of interest. We developed a simple method that uses a chi-square-based scoring function to determine the likelihood of MEDLINE citations containing genetic relevant topic. Our procedure requires construction of a genetic and a nongenetic domain document corpus. We used MeSH descriptors assigned to MEDLINE citations for this categorization task. We compared frequencies of MeSH descriptors between two corpora applying chi-square test. A MeSH descriptor was considered to be a positive indicator if its relative observed frequency in the genetic domain corpus was greater than its relative observed frequency in the nongenetic domain corpus. The output of the proposed method is a list of scores for all the citations, with the highest score given to those citations containing MeSH descriptors typical for the genetic domain. Validation was done on a set of 734 manually annotated MEDLINE citations. It achieved predictive accuracy of 0.87 with 0.69 recall and 0.64 precision. We evaluated the method by comparing it to three machine-learning algorithms (support vector machines, decision trees, naïve Bayes). Although the differences were not statistically significantly different, results showed that our chi-square scoring performs as good as compared machine-learning algorithms. We suggest that the chi-square scoring is an effective solution to help categorize MEDLINE citations. The algorithm is implemented in the BITOLA literature-based discovery support system as a preprocessor for gene symbol disambiguation process.

Indexing and Retrieval in ERIC: The 20th Year.

ERIC Educational Resources Information Center

Barnett, Lynn

This brief review of the Educational Resources Information Center (ERIC) system is intended to make users more aware of (1) the system as a whole, (2) the process of indexing educational literature for the database, and (3) the role of the Thesaurus of ERIC Descriptors in the overall information dissemination process. An overview of the ERIC…

Mining semantic networks of bioinformatics e-resources from the literature

PubMed Central

2011-01-01

Background There have been a number of recent efforts (e.g. BioCatalogue, BioMoby) to systematically catalogue bioinformatics tools, services and datasets. These efforts rely on manual curation, making it difficult to cope with the huge influx of various electronic resources that have been provided by the bioinformatics community. We present a text mining approach that utilises the literature to automatically extract descriptions and semantically profile bioinformatics resources to make them available for resource discovery and exploration through semantic networks that contain related resources. Results The method identifies the mentions of resources in the literature and assigns a set of co-occurring terminological entities (descriptors) to represent them. We have processed 2,691 full-text bioinformatics articles and extracted profiles of 12,452 resources containing associated descriptors with binary and tf*idf weights. Since such representations are typically sparse (on average 13.77 features per resource), we used lexical kernel metrics to identify semantically related resources via descriptor smoothing. Resources are then clustered or linked into semantic networks, providing the users (bioinformaticians, curators and service/tool crawlers) with a possibility to explore algorithms, tools, services and datasets based on their relatedness. Manual exploration of links between a set of 18 well-known bioinformatics resources suggests that the method was able to identify and group semantically related entities. Conclusions The results have shown that the method can reconstruct interesting functional links between resources (e.g. linking data types and algorithms), in particular when tf*idf-like weights are used for profiling. This demonstrates the potential of combining literature mining and simple lexical kernel methods to model relatedness between resource descriptors in particular when there are few features, thus potentially improving the resource description, discovery and exploration process. The resource profiles are available at http://gnode1.mib.man.ac.uk/bioinf/semnets.html PMID:21388573

Detection of illegal transfer of videos over the Internet

NASA Astrophysics Data System (ADS)

Chaisorn, Lekha; Sainui, Janya; Manders, Corey

2010-07-01

In this paper, a method for detecting infringements or modifications of a video in real-time is proposed. The method first segments a video stream into shots, after which it extracts some reference frames as keyframes. This process is performed employing a Singular Value Decomposition (SVD) technique developed in this work. Next, for each input video (represented by its keyframes), ordinal-based signature and SIFT (Scale Invariant Feature Transform) descriptors are generated. The ordinal-based method employs a two-level bitmap indexing scheme to construct the index for each video signature. The first level clusters all input keyframes into k clusters while the second level converts the ordinal-based signatures into bitmap vectors. On the other hand, the SIFT-based method directly uses the descriptors as the index. Given a suspect video (being streamed or transferred on the Internet), we generate the signature (ordinal and SIFT descriptors) then we compute similarity between its signature and those signatures in the database based on ordinal signature and SIFT descriptors separately. For similarity measure, besides the Euclidean distance, Boolean operators are also utilized during the matching process. We have tested our system by performing several experiments on 50 videos (each about 1/2 hour in duration) obtained from the TRECVID 2006 data set. For experiments set up, we refer to the conditions provided by TRECVID 2009 on "Content-based copy detection" task. In addition, we also refer to the requirements issued in the call for proposals by MPEG standard on the similar task. Initial result shows that our framework is effective and robust. As compared to our previous work, on top of the achievement we obtained by reducing the storage space and time taken in the ordinal based method, by introducing the SIFT features, we could achieve an overall accuracy in F1 measure of about 96% (improved about 8%).

Improved Prediction of Blood-Brain Barrier Permeability Through Machine Learning with Combined Use of Molecular Property-Based Descriptors and Fingerprints.

PubMed

Yuan, Yaxia; Zheng, Fang; Zhan, Chang-Guo

2018-03-21

Blood-brain barrier (BBB) permeability of a compound determines whether the compound can effectively enter the brain. It is an essential property which must be accounted for in drug discovery with a target in the brain. Several computational methods have been used to predict the BBB permeability. In particular, support vector machine (SVM), which is a kernel-based machine learning method, has been used popularly in this field. For SVM training and prediction, the compounds are characterized by molecular descriptors. Some SVM models were based on the use of molecular property-based descriptors (including 1D, 2D, and 3D descriptors) or fragment-based descriptors (known as the fingerprints of a molecule). The selection of descriptors is critical for the performance of a SVM model. In this study, we aimed to develop a generally applicable new SVM model by combining all of the features of the molecular property-based descriptors and fingerprints to improve the accuracy for the BBB permeability prediction. The results indicate that our SVM model has improved accuracy compared to the currently available models of the BBB permeability prediction.

Dyspnea descriptors translated from English to Portuguese: application in obese patients and in patients with cardiorespiratory diseases.

PubMed

Teixeira, Christiane Aires; Rodrigues Júnior, Antonio Luiz; Straccia, Luciana Cristina; Vianna, Elcio Dos Santos Oliveira; Silva, Geruza Alves da; Martinez, José Antônio Baddini

2011-01-01

To investigate the usefulness of descriptive terms applied to the sensation of dyspnea (dyspnea descriptors) that were developed in English and translated to Brazilian Portuguese in patients with four distinct clinical conditions that can be accompanied by dyspnea. We translated, from English to Brazilian Portuguese, a list of 15 dyspnea descriptors reported in a study conducted in the USA. Those 15 descriptors were applied in 50 asthma patients, 50 COPD patients, 30 patients with heart failure, and 50 patients with class II or III obesity. The three best descriptors, as selected by the patients, were studied by cluster analysis. Potential associations between the identified clusters and the four clinical conditions were also investigated. The use of this set of descriptors led to a solution with nine clusters, designated expiração (exhalation), fome de ar (air hunger), sufoco (suffocating), superficial (shallow), rápido (rapid), aperto (tight), falta de ar (shortness of breath), trabalho (work), and inspiração (inhalation). Overlapping of the descriptors was quite common among the patients, regardless of their clinical condition. Asthma, COPD, and heart failure were significantly associated with the inspiração cluster. Heart failure was also associated with the trabalho cluster, whereas obesity was not associated with any of the clusters. In our study sample, the application of dyspnea descriptors translated from English to Portuguese led to the identification of distinct clusters, some of which were similar to those identified in a study conducted in the USA. The translated descriptors were less useful than were those developed in Brazil regarding their ability to generate significant associations among the clinical conditions investigated here.

Direct memory access transfer completion notification

DOEpatents

Chen, Dong; Giampapa, Mark E.; Heidelberger, Philip; Kumar, Sameer; Parker, Jeffrey J.; Steinmacher-Burow, Burkhard D.; Vranas, Pavlos

2010-07-27

Methods, compute nodes, and computer program products are provided for direct memory access (`DMA`) transfer completion notification. Embodiments include determining, by an origin DMA engine on an origin compute node, whether a data descriptor for an application message to be sent to a target compute node is currently in an injection first-in-first-out (`FIFO`) buffer in dependence upon a sequence number previously associated with the data descriptor, the total number of descriptors currently in the injection FIFO buffer, and the current sequence number for the newest data descriptor stored in the injection FIFO buffer; and notifying a processor core on the origin DMA engine that the message has been sent if the data descriptor for the message is not currently in the injection FIFO buffer.

Character context: a shape descriptor for Arabic handwriting recognition

NASA Astrophysics Data System (ADS)

Mudhsh, Mohammed; Almodfer, Rolla; Duan, Pengfei; Xiong, Shengwu

2017-11-01

In the handwriting recognition field, designing good descriptors are substantial to obtain rich information of the data. However, the handwriting recognition research of a good descriptor is still an open issue due to unlimited variation in human handwriting. We introduce a "character context descriptor" that efficiently dealt with the structural characteristics of Arabic handwritten characters. First, the character image is smoothed and normalized, then the character context descriptor of 32 feature bins is built based on the proposed "distance function." Finally, a multilayer perceptron with regularization is used as a classifier. On experimentation with a handwritten Arabic characters database, the proposed method achieved a state-of-the-art performance with recognition rate equal to 98.93% and 99.06% for the 66 and 24 classes, respectively.

Adjacent bin stability evaluating for feature description

NASA Astrophysics Data System (ADS)

Nie, Dongdong; Ma, Qinyong

2018-04-01

Recent study improves descriptor performance by accumulating stability votes for all scale pairs to compose the local descriptor. We argue that the stability of a bin depends on the differences across adjacent pairs more than the differences across all scale pairs, and a new local descriptor is composed based on the hypothesis. A series of SIFT descriptors are extracted from multiple scales firstly. Then the difference value of the bin across adjacent scales is calculated, and the stability value of a bin is calculated based on it and accumulated to compose the final descriptor. The performance of the proposed method is evaluated with two popular matching datasets, and compared with other state-of-the-art works. Experimental results show that the proposed method performs satisfactorily.

RPBS: Rotational Projected Binary Structure for point cloud representation

NASA Astrophysics Data System (ADS)

Fang, Bin; Zhou, Zhiwei; Ma, Tao; Hu, Fangyu; Quan, Siwen; Ma, Jie

2018-03-01

In this paper, we proposed a novel three-dimension local surface descriptor named RPBS for point cloud representation. First, points cropped form the query point within a predefined radius is regard as a local surface patch. Then pose normalization is done to the local surface to equip our descriptor with the invariance to rotation transformation. To obtain more information about the cropped surface, multi-view representation is formed by successively rotating it along the coordinate axis. Further, orthogonal projections to the three coordinate plane are adopted to construct two-dimension distribution matrixes, and binarization is applied to each matrix by following the rule that whether the grid is occupied, if yes, set the grid one, otherwise zero. We calculate the binary maps from all the viewpoints and concatenate them together as the final descriptor. Comparative experiments for evaluating our proposed descriptor is conducted on the standard dataset named Bologna with several state-of-the-art 3D descriptors, and results show that our descriptor achieves the best performance on feature matching experiments.

Branch length similarity entropy-based descriptors for shape representation

NASA Astrophysics Data System (ADS)

Kwon, Ohsung; Lee, Sang-Hee

2017-11-01

In previous studies, we showed that the branch length similarity (BLS) entropy profile could be successfully used for the shape recognition such as battle tanks, facial expressions, and butterflies. In the present study, we proposed new descriptors, roundness, symmetry, and surface roughness, for the recognition, which are more accurate and fast in the computation than the previous descriptors. The roundness represents how closely a shape resembles to a circle, the symmetry characterizes how much one shape is similar with another when the shape is moved in flip, and the surface roughness quantifies the degree of vertical deviations of a shape boundary. To evaluate the performance of the descriptors, we used the database of leaf images with 12 species. Each species consisted of 10 - 20 leaf images and the total number of images were 160. The evaluation showed that the new descriptors successfully discriminated the leaf species. We believe that the descriptors can be a useful tool in the field of pattern recognition.

Gun bore flaw image matching based on improved SIFT descriptor

NASA Astrophysics Data System (ADS)

Zeng, Luan; Xiong, Wei; Zhai, You

2013-01-01

In order to increase the operation speed and matching ability of SIFT algorithm, the SIFT descriptor and matching strategy are improved. First, a method of constructing feature descriptor based on sector area is proposed. By computing the gradients histogram of location bins which are parted into 6 sector areas, a descriptor with 48 dimensions is constituted. It can reduce the dimension of feature vector and decrease the complexity of structuring descriptor. Second, it introduce a strategy that partitions the circular region into 6 identical sector areas starting from the dominate orientation. Consequently, the computational complexity is reduced due to cancellation of rotation operation for the area. The experimental results indicate that comparing with the OpenCV SIFT arithmetic, the average matching speed of the new method increase by about 55.86%. The matching veracity can be increased even under some variation of view point, illumination, rotation, scale and out of focus. The new method got satisfied results in gun bore flaw image matching. Keywords: Metrology, Flaw image matching, Gun bore, Feature descriptor

Rapid prediction of chemical metabolism by human UDP-glucuronosyltransferase isoforms using quantum chemical descriptors derived with the electronegativity equalization method.

PubMed

Sorich, Michael J; McKinnon, Ross A; Miners, John O; Winkler, David A; Smith, Paul A

2004-10-07

This study aimed to evaluate in silico models based on quantum chemical (QC) descriptors derived using the electronegativity equalization method (EEM) and to assess the use of QC properties to predict chemical metabolism by human UDP-glucuronosyltransferase (UGT) isoforms. Various EEM-derived QC molecular descriptors were calculated for known UGT substrates and nonsubstrates. Classification models were developed using support vector machine and partial least squares discriminant analysis. In general, the most predictive models were generated with the support vector machine. Combining QC and 2D descriptors (from previous work) using a consensus approach resulted in a statistically significant improvement in predictivity (to 84%) over both the QC and 2D models and the other methods of combining the descriptors. EEM-derived QC descriptors were shown to be both highly predictive and computationally efficient. It is likely that EEM-derived QC properties will be generally useful for predicting ADMET and physicochemical properties during drug discovery.

A matter of scale: apparent niche differentiation of diploid and tetraploid plants may depend on extent and grain of analysis.

PubMed

Kirchheimer, Bernhard; Schinkel, Christoph C F; Dellinger, Agnes S; Klatt, Simone; Moser, Dietmar; Winkler, Manuela; Lenoir, Jonathan; Caccianiga, Marco; Guisan, Antoine; Nieto-Lugilde, Diego; Svenning, Jens-Christian; Thuiller, Wilfried; Vittoz, Pascal; Willner, Wolfgang; Zimmermann, Niklaus E; Hörandl, Elvira; Dullinger, Stefan

2016-03-22

Emerging polyploids may depend on environmental niche shifts for successful establishment. Using the alpine plant Ranunculus kuepferi as a model system, we explore the niche shift hypothesis at different spatial resolutions and in contrasting parts of the species range. European Alps. We sampled 12 individuals from each of 102 populations of R. kuepferi across the Alps, determined their ploidy levels, derived coarse-grain (100 × 100 m) environmental descriptors for all sampling sites by downscaling WorldClim maps, and calculated fine-scale environmental descriptors (2 × 2 m) from indicator values of the vegetation accompanying the sampled individuals. Both coarse and fine-scale variables were further computed for 8239 vegetation plots from across the Alps. Subsequently, we compared niche optima and breadths of diploid and tetraploid cytotypes by combining principal components analysis and kernel smoothing procedures. Comparisons were done separately for coarse and fine-grain data sets and for sympatric, allopatric and the total set of populations. All comparisons indicate that the niches of the two cytotypes differ in optima and/or breadths, but results vary in important details. The whole-range analysis suggests differentiation along the temperature gradient to be most important. However, sympatric comparisons indicate that this climatic shift was not a direct response to competition with diploid ancestors. Moreover, fine-grained analyses demonstrate niche contraction of tetraploids, especially in the sympatric range, that goes undetected with coarse-grained data. Although the niche optima of the two cytotypes differ, separation along ecological gradients was probably less decisive for polyploid establishment than a shift towards facultative apomixis, a particularly effective strategy to avoid minority cytotype exclusion. In addition, our results suggest that coarse-grained analyses overestimate niche breadths of widely distributed taxa. Niche comparison analyses should hence be conducted at environmental data resolutions appropriate for the organism and question under study.

The effects of variant descriptors on the potential effectiveness of plain packaging.

PubMed

Borland, Ron; Savvas, Steven

2014-01-01

To examine the effects that variant descriptor labels on cigarette packs have on smokers' perceptions of those packs and the cigarettes contained within. As part of two larger web-based studies (each involved 160 young adult ever-smokers 18-29 years old), respondents were shown a computer image of a plain cigarette pack and sets of related variant descriptors. The sets included terms that varied in terms of descriptors of colours as names, flavour strength, degrees of filter venting, filter types, quality, type of cigarette and numbers. For each set, respondents rated the highest and lowest of two or three of the following four characteristics: quality, strongest or weakest in taste, delivers most or least tar/nicotine, and most or least level of harm. There were significant differences on all four ratings. Quality ratings were the least differentiated. Except for colour descriptors, where 'Gold' rated high in quality but medium in other ratings, ratings of quality, harm, strength and delivery were all positively associated when rated on the same descriptors. Descriptor labels on cigarette packs, can affect smokers' perceptions of the characteristics of the cigarettes contained within. Therefore, they are a potential means by which product differentiation can occur. In particular, having variants differing in perceived strength while not differing in deliveries of harmful ingredients is particularly problematic. Any packaging policy should take into account the possibility that variant descriptors can mislead smokers into making inappropriate product attributions.

ADME evaluation in drug discovery. 1. Applications of genetic algorithms to the prediction of blood-brain partitioning of a large set of drugs.

PubMed

Hou, Tingjun; Xu, Xiaojie

2002-12-01

In this study, the relationships between the brain-blood concentration ratio of 96 structurally diverse compounds with a large number of structurally derived descriptors were investigated. The linear models were based on molecular descriptors that can be calculated for any compound simply from a knowledge of its molecular structure. The linear correlation coefficients of the models were optimized by genetic algorithms (GAs), and the descriptors used in the linear models were automatically selected from 27 structurally derived descriptors. The GA optimizations resulted in a group of linear models with three or four molecular descriptors with good statistical significance. The change of descriptor use as the evolution proceeds demonstrates that the octane/water partition coefficient and the partial negative solvent-accessible surface area multiplied by the negative charge are crucial to brain-blood barrier permeability. Moreover, we found that the predictions using multiple QSPR models from GA optimization gave quite good results in spite of the diversity of structures, which was better than the predictions using the best single model. The predictions for the two external sets with 37 diverse compounds using multiple QSPR models indicate that the best linear models with four descriptors are sufficiently effective for predictive use. Considering the ease of computation of the descriptors, the linear models may be used as general utilities to screen the blood-brain barrier partitioning of drugs in a high-throughput fashion.

A new texture descriptor based on local micro-pattern for detection of architectural distortion in mammographic images

NASA Astrophysics Data System (ADS)

de Oliveira, Helder C. R.; Moraes, Diego R.; Reche, Gustavo A.; Borges, Lucas R.; Catani, Juliana H.; de Barros, Nestor; Melo, Carlos F. E.; Gonzaga, Adilson; Vieira, Marcelo A. C.

2017-03-01

This paper presents a new local micro-pattern texture descriptor for the detection of Architectural Distortion (AD) in digital mammography images. AD is a subtle contraction of breast parenchyma that may represent an early sign of breast cancer. Due to its subtlety and variability, AD is more difficult to detect compared to microcalcifications and masses, and is commonly found in retrospective evaluations of false-negative mammograms. Several computer-based systems have been proposed for automatic detection of AD, but their performance are still unsatisfactory. The proposed descriptor, Local Mapped Pattern (LMP), is a generalization of the Local Binary Pattern (LBP), which is considered one of the most powerful feature descriptor for texture classification in digital images. Compared to LBP, the LMP descriptor captures more effectively the minor differences between the local image pixels. Moreover, LMP is a parametric model which can be optimized for the desired application. In our work, the LMP performance was compared to the LBP and four Haralick's texture descriptors for the classification of 400 regions of interest (ROIs) extracted from clinical mammograms. ROIs were selected and divided into four classes: AD, normal tissue, microcalcifications and masses. Feature vectors were used as input to a multilayer perceptron neural network, with a single hidden layer. Results showed that LMP is a good descriptor to distinguish AD from other anomalies in digital mammography. LMP performance was slightly better than the LBP and comparable to Haralick's descriptors (mean classification accuracy = 83%).

A robust H∞-tracking design for uncertain Takagi-Sugeno fuzzy systems with unknown premise variables using descriptor redundancy approach

NASA Astrophysics Data System (ADS)

Hassan Asemani, Mohammad; Johari Majd, Vahid

2015-12-01

This paper addresses a robust H∞ fuzzy observer-based tracking design problem for uncertain Takagi-Sugeno fuzzy systems with external disturbances. To have a practical observer-based controller, the premise variables of the system are assumed to be not measurable in general, which leads to a more complex design process. The tracker is synthesised based on a fuzzy Lyapunov function approach and non-parallel distributed compensation (non-PDC) scheme. Using the descriptor redundancy approach, the robust stability conditions are derived in the form of strict linear matrix inequalities (LMIs) even in the presence of uncertainties in the system, input, and output matrices simultaneously. Numerical simulations are provided to show the effectiveness of the proposed method.

Disruptive Civil Technologies: Six Technologies With Potential Impacts on US Interests Out to 2025

DTIC Science & Technology

2008-04-01

power (geopolitical, military, economic, or social cohesion). The six disruptive technologies were identified through a process carried out by...clustering, development of technology descriptors, screening, and prioritizing, analysts down-selected from 102 potentially disruptive technologies . They

DDC Descriptor Frequencies.

ERIC Educational Resources Information Center

Klingbiel, Paul H.; Jacobs, Charles R.

This report summarizes the frequency of use of the 7144 descriptors used for indexing technical reports in the Defense Documentation Center (DDC) collection. The descriptors are arranged alphabetically in the first section and by frequency in the second section. The frequency data cover about 427,000 AD documents spanning the interval from March…

MultiDK: A Multiple Descriptor Multiple Kernel Approach for Molecular Discovery and Its Application to Organic Flow Battery Electrolytes.

PubMed

Kim, Sungjin; Jinich, Adrián; Aspuru-Guzik, Alán

2017-04-24

We propose a multiple descriptor multiple kernel (MultiDK) method for efficient molecular discovery using machine learning. We show that the MultiDK method improves both the speed and accuracy of molecular property prediction. We apply the method to the discovery of electrolyte molecules for aqueous redox flow batteries. Using multiple-type-as opposed to single-type-descriptors, we obtain more relevant features for machine learning. Following the principle of "wisdom of the crowds", the combination of multiple-type descriptors significantly boosts prediction performance. Moreover, by employing multiple kernels-more than one kernel function for a set of the input descriptors-MultiDK exploits nonlinear relations between molecular structure and properties better than a linear regression approach. The multiple kernels consist of a Tanimoto similarity kernel and a linear kernel for a set of binary descriptors and a set of nonbinary descriptors, respectively. Using MultiDK, we achieve an average performance of r 2 = 0.92 with a test set of molecules for solubility prediction. We also extend MultiDK to predict pH-dependent solubility and apply it to a set of quinone molecules with different ionizable functional groups to assess their performance as flow battery electrolytes.

Application of the artificial neural network in quantitative structure-gradient elution retention relationship of phenylthiocarbamyl amino acids derivatives.

PubMed

Tham, S Y; Agatonovic-Kustrin, S

2002-05-15

Quantitative structure-retention relationship(QSRR) method was used to model reversed-phase high-performance liquid chromatography (RP-HPLC) separation of 18 selected amino acids. Retention data for phenylthiocarbamyl (PTC) amino acids derivatives were obtained using gradient elution on ODS column with mobile phase of varying acetonitrile, acetate buffer and containing 0.5 ml/l of triethylamine (TEA). Molecular structure of each amino acid was encoded with 36 calculated molecular descriptors. The correlation between the molecular descriptors and the retention time of the compounds in the calibration set was established using the genetic neural network method. A genetic algorithm (GA) was used to select important molecular descriptors and supervised artificial neural network (ANN) was used to correlate mobile phase composition and selected descriptors with the experimentally derived retention times. Retention time values were used as the network's output and calculated molecular descriptors and mobile phase composition as the inputs. The best model with five input descriptors was chosen, and the significance of the selected descriptors for amino acid separation was examined. Results confirmed the dominant role of the organic modifier in such chromatographic systems in addition to lipophilicity (log P) and molecular size and shape (topological indices) of investigated solutes.

Effective structural descriptors for natural and engineered radioactive waste confinement barriers

NASA Astrophysics Data System (ADS)

Lemmens, Laurent; Rogiers, Bart; De Craen, Mieke; Laloy, Eric; Jacques, Diederik; Huysmans, Marijke; Swennen, Rudy; Urai, Janos L.; Desbois, Guillaume

2017-04-01

The microstructure of a radioactive waste confinement barrier strongly influences its flow and transport properties. Numerical flow and transport simulations for these porous media at the pore scale therefore require input data that describe the microstructure as accurately as possible. To date, no imaging method can resolve all heterogeneities within important radioactive waste confinement barrier materials as hardened cement paste and natural clays at the micro scale (nm-cm). Therefore, it is necessary to merge information from different 2D and 3D imaging methods using porous media reconstruction techniques. To qualitatively compare the results of different reconstruction techniques, visual inspection might suffice. To quantitatively compare training-image based algorithms, Tan et al. (2014) proposed an algorithm using an analysis of distance. However, the ranking of the algorithm depends on the choice of the structural descriptor, in their case multiple-point or cluster-based histograms. We present here preliminary work in which we will review different structural descriptors and test their effectiveness, for capturing the main structural characteristics of radioactive waste confinement barrier materials, to determine the descriptors to use in the analysis of distance. The investigated descriptors are particle size distributions, surface area distributions, two point probability functions, multiple point histograms, linear functions and two point cluster functions. The descriptor testing consists of stochastically generating realizations from a reference image using the simulated annealing optimization procedure introduced by Karsanina et al. (2015). This procedure basically minimizes the differences between pre-specified descriptor values associated with the training image and the image being produced. The most efficient descriptor set can therefore be identified by comparing the image generation quality among the tested descriptor combinations. The assessment of the quality of the simulations will be made by combining all considered descriptors. Once the set of the most efficient descriptors is determined, they can be used in the analysis of distance, to rank different reconstruction algorithms in a more objective way in future work. Karsanina MV, Gerke KM, Skvortsova EB, Mallants D (2015) Universal Spatial Correlation Functions for Describing and Reconstructing Soil Microstructure. PLoS ONE 10(5): e0126515. doi:10.1371/journal.pone.0126515 Tan, Xiaojin, Pejman Tahmasebi, and Jef Caers. "Comparing training-image based algorithms using an analysis of distance." Mathematical Geosciences 46.2 (2014): 149-169.

Using the Identity Processing Style Q-Sort to Examine Identity Styles of Turkish Young Adults

ERIC Educational Resources Information Center

Eryigit, Suna; Kerpelman, Jennifer

2009-01-01

This paper reports on two studies with Turkish young adults that used the Turkish version of the Identity Processing Style Q-Sort (IPSQ). The IPSQ is based on Berzonsky's informational, normative, and diffused identity styles. Participants sort descriptors of the styles into columns ranging from most to least like them. Patterns in Turkish young…

Chemodiversity and molecular plasticity: recognition processes as explored by property spaces.

PubMed

Vistoli, Giulio; Pedretti, Alessandro; Testa, Bernard

2011-06-01

In the last few years, a need to account for molecular flexibility in drug-design methodologies has emerged, even if the dynamic behavior of molecular properties is seldom made explicit. For a flexible molecule, it is indeed possible to compute different values for a given conformation-dependent property and the ensemble of such values defines a property space that can be used to describe its molecular variability; a most representative case is the lipophilicity space. In this review, a number of applications of lipophilicity space and other property spaces are presented, showing that this concept can be fruitfully exploited: to investigate the constraints exerted by media of different levels of structural organization, to examine processes of molecular recognition and binding at an atomic level, to derive informative descriptors to be included in quantitative structure--activity relationships and to analyze protein simulations extracting the relevant information. Much molecular information is neglected in the descriptors used by medicinal chemists, while the concept of property space can fill this gap by accounting for the often-disregarded dynamic behavior of both small ligands and biomacromolecules. Property space also introduces some innovative concepts such as molecular sensitivity and plasticity, which appear best suited to explore the ability of a molecule to adapt itself to the environment variously modulating its property and conformational profiles. Globally, such concepts can enhance our understanding of biological phenomena providing fruitful descriptors in drug-design and pharmaceutical sciences.

The two faces of hydrogen-bond strength on triple AAA-DDD arrays.

PubMed

Lopez, Alfredo Henrique Duarte; Caramori, Giovanni Finoto; Coimbra, Daniel Fernando; Parreira, Renato Luis Tame; da Silva, Éder Henrique

2013-12-02

Systems that are connected through multiple hydrogen bonds are the cornerstone of molecular recognition processes in biology, and they are increasingly being employed in supramolecular chemistry, specifically in molecular self-assembly processes. For this reason, the effects of different substituents (NO2, CN, F, Cl, Br, OCH3 and NH2) on the electronic structure, and consequently on the magnitude of hydrogen bonds in triple AAA-DDD arrays (A=acceptor, D=donor) were evaluated in the light of topological [electron localization function (ELF) and quantum theory of atoms in molecules (QTAIM)], energetic [Su-Li energy-decomposition analysis (EDA) and natural bond orbital analysis (NBO)], and geometrical analysis. The results based on local H-bond descriptors (geometries, QTAIM, ELF, and NBO) indicate that substitutions with electron-withdrawing groups on the AAA module tend to strengthen, whereas electron-donating substituents tend to weaken the covalent character of the AAA-DDD intermolecular H-bonds, and also indicate that the magnitude of the effect is dependent on the position of substitution. In contrast, Su-Li EDA results show an opposite behavior when compared to local H-bond descriptors, indicating that electron-donating substituents tend to increase the magnitude of H-bonds in AAA-DDD arrays, and thus suggesting that the use of local H-bond descriptors describes the nature of H bonds only partially, not providing enough insight about the strength of such H bonds. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Response of Farmland Bird Communities to Agricultural Intensity as Influenced by Its Spatial Aggregation

PubMed Central

Teillard, Félix; Jiguet, Frédéric; Tichit, Muriel

2015-01-01

The shape of the relationship between biodiversity and agricultural intensity determines the range of intensities that should be targeted by conservation policies to obtain the greatest environmental benefits. Although preliminary evidence of this relationship exists, the influence of the spatial arrangement of intensity on biodiversity remains untested. We conducted a nationwide study linking agricultural intensity and its spatial arrangement to a farmland bird community of 22 species. Intensity was described with a continuous indicator based on Input Cost per hectare, which was relevant for both livestock and crop production. We used the French Breeding Bird Survey to compute several descriptors of the farmland bird community along the intensity gradient and tested for the significance of an interaction effect between intensity and its spatial aggregation on these descriptors. We found that the bird community was comprised of both winner and loser species with regard to intensity. The community composition descriptors (trophic level, specialisation, and specialisation for grassland indices) displayed non-linear relationships to intensity, with steeper slopes in the lower intensity range. We found a significant interaction effect between intensity and its spatial aggregation on the grassland specialisation index of the bird community; the effect of agricultural intensity was strengthened by its spatial aggregation. We suggest that an opportunity to improve the effectiveness of conservation policies exists by targeting measures in areas where intensity is moderate to low and aggregated. The effect of the aggregation of agricultural intensity on biodiversity should be considered in other scales and taxa when developing optimal policy targeting and intensity allocation strategies. PMID:25799552

Virtual lock-and-key approach: the in silico revival of Fischer model by means of molecular descriptors.

PubMed

Lauria, Antonino; Tutone, Marco; Almerico, Anna Maria

2011-09-01

In the last years the application of computational methodologies in the medicinal chemistry fields has found an amazing development. All the efforts were focused on the searching of new leads featuring a close affinity on a specific biological target. Thus, different molecular modeling approaches in simulation of molecular behavior for a specific biological target were employed. In spite of the increasing reliability of computational methodologies, not always the designed lead, once synthesized and screened, are suitable for the chosen biological target. To give another chance to these compounds, this work tries to resume the old concept of Fischer lock-and-key model. The same can be done for the "re-purposing" of old drugs. In fact, it is known that drugs may have many physiological targets, therefore it may be useful to identify them. This aspect, called "polypharmacology", is known to be therapeutically essential in the different treatments. The proposed protocol, the virtual lock-and-key approach (VLKA), consists in the "virtualization" of biological targets through the respectively known inhibitors. In order to release a real lock it is necessary the key fits the pins of the lock. The molecular descriptors could be considered as pins. A tested compound can be considered a potential inhibitor of a biological target if the values of its molecular descriptors fall in the calculated range values for the set of known inhibitors. The proposed protocol permits to transform a biological target in a "lock model" starting from its known inhibitors. To release a real lock all pins must fit. In the proposed protocol, it was supposed that the higher is the number of fit pins, the higher will be the affinity to the considered biological target. Therefore, each biological target was converted in a sequence of "weighted" molecular descriptor range values (locks) by using the structural features of the known inhibitors. Each biological target lock was tested by performing a molecular descriptors "fitting" on known inhibitors not used in the model construction (keys or test set). The results showed a good predictive capability of the protocol (confidence level 80%). This method gives interesting and convenient results because of the user-defined descriptors and biological targets choice in the process of new inhibitors discovery. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

How good is good? Students and assessors' perceptions of qualitative markers of performance.

PubMed

Ma, Heung Kan; Min, Cynthia; Neville, Alan; Eva, Kevin

2013-01-01

Qualitative markers of performance are routinely used for medical student assessment, though the extent to which such markers can be readily translated to actionable pieces of information remains uncertain. To explore (a) the perceived value to be indicated by descriptor phrases commonly used for describing student performance, (b) the perceived weight of the different performance domains (e.g. communication skills, work ethic, knowledge base, etc), and (c) whether or not the perceived value of the descriptors changes as a function of the performance domains. Five domains of performance were identified from the thematic coding of past medical student transcripts (N = 156). From the transcripts, 91 distinct descriptors indicating the language commonly used by assessors were also identified. From the list of 91 descriptors, Thurstone's method of equal-appearing intervals was used to extract 10 descriptors that were representative of the continuum of student performance. A modified paired comparisons method was then used to enable the relative ranking of each of 10 descriptors combined with each of 5 different domains of performance. A web-based survey was used to collect responses from participants (N = 209), which consisted of medical students and faculty members who were previously involved in student assessment. Results demonstrated that respondents did not simply sum positive and negative descriptors in a uniform manner. Rather, comments on some domains (e.g., "ability to apply patient centred medicine") were seen as particularly positive when associated with positive descriptors but not particularly negative when associated with negative descriptors. For others (e.g., "receptivity and responsiveness to feedback") the reverse was true. Comments on "knowledge-base" elicited a relatively muted perception at both ends of the scale. Finally, the results also revealed moderate misalignment in the perceptions of assessors and students. The findings from this study suggest that the use of any given descriptor conveys slightly different meaning dependent on the context in which it is used. This helps to address some key issues surrounding the application of qualitative markers to performance assessment in medical education.

Diagnostic performance and reproducibility of T2w based and diffusion weighted imaging (DWI) based PI-RADSv2 lexicon descriptors for prostate MRI.

PubMed

Benndorf, Matthias; Hahn, Felix; Krönig, Malte; Jilg, Cordula Annette; Krauss, Tobias; Langer, Mathias; Dovi-Akué, Philippe

2017-08-01

To examine the diagnostic performance of PI-RADSv2 T2w and diffusion weighted imaging (DWI) based lexicon descriptors, inter-observer agreement for descriptor assignment and diagnostic accuracy of the PI-RADSv2 assessment categories for multiparametric prostate MRI. 176 lesions in 79 consecutive patients are analyzed, lesions are histopathologically verified by MRI-ultrasound fusion biopsy. All lesions are rated according to the PI-RADSv2 lexicon, descriptors for T2w and DWI sequences and resulting assessment categories are assigned by two independent blinded radiologists. We perform receiver-operating-characteristic analysis using the assessment categories. To analyze inter-observer agreement, we calculate weighted kappa values for assessment category assignment and unweighted kappa values for descriptor assignment. PI-RADSv2 assessment categories yield an area under the curve of 0.76/0.74 (radiologist 1/radiologist 2), P >0.05. Weighted kappa for agreement is 0.601 in the peripheral zone and 0.580 in the transition zone. We detect a difference in the cancer rate for PI-RADSv2 category 3 between peripheral zone (32%) and transition zone (12%), P <0.05. We obtain moderate agreement at most for descriptor assignment with kappa values ranging from 0.082 (T2w shape in the transition zone) to 0.407 (T2w signal intensity in the peripheral zone) and 0.493 (ADC pattern in the peripheral zone). Our analysis corroborates typical descriptors for benign/malignant lesions, but also reveals insights into potential pitfalls - T2w wedge shaped lesions in the peripheral zone have a considerable cancer rate, despite being labelled category 2 in the lexicon. Agreement for descriptor assignment in the PI-RADSv2 lexicon is at most moderate in our study. Typical descriptors for benign and malignant lesions are validated, whereas the discriminatory power of some descriptors is challenged. The difference in the cancer rate for PI-RADSv2 category 3 between peripheral zone and transition zone should be considered when management recommendations are linked to assessment categories in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

How young water fractions can delineate travel time distributions in contrasting catchments

NASA Astrophysics Data System (ADS)

Lutz, Stefanie; Zink, Matthias; Merz, Ralf

2017-04-01

Travel time distributions (TTDs) are crucial descriptors of flow and transport processes in catchments. Tracking fluxes of environmental tracers such as stable water isotopes offers a practicable method to determine TTDs. The mean transit time (MTT) is the most commonly reported statistic of TTDs; however, MTT assessments are prone to large aggregation biases resulting from spatial heterogeneity and non-stationarity in real-world catchments. Recently, the young water fraction (Fyw) has been introduced as a more robust statistic that can be derived from seasonal tracer cycles. In this study, we aimed at improving the assessment of TTDs by using Fyw as additional information in lumped isotope models. First, we calculated Fyw from monthly δ18O-samples for 24 contrasting sub-catchments in a meso-scale catchment (3300 km2). Fyw ranged from 0.01 to 0.27 (mean= 0.11) and was not significantly correlated with catchment characteristics (e.g., mean slope, catchment area, and baseflow index) apart from the dominant soil type. Second, assuming gamma-shaped TTDs, we determined time-invariant TTDs for each sub-catchment by optimization of lumped isotope models using the convolution integral method. Whereas multiple optimization runs for the same sub-catchment showed a wide range of TTD parameters, the use of Fyw as additional information allowed constraining this range and thus improving the assessment of MTTs. Hence, the best model fit to observed isotope data might not be the desired solution, as the resulting TTD might define a young water fraction non-consistent with the tracer-cycle based Fyw. Given that the latter is a robust descriptor of fast-flow contribution, isotope models should instead aim at accurately describing both Fyw and the isotope time series in order to improve our understanding of flow and transport in catchments.

Hearing aid fine-tuning based on Dutch descriptions.

PubMed

Thielemans, Thijs; Pans, Donné; Chenault, Michelene; Anteunis, Lucien

2017-07-01

The aim of this study was to derive an independent fitting assistant based on expert consensus. Two questions were asked: (1) what (Dutch) terms do hearing impaired listeners use nowadays to describe their specific hearing aid fitting problems? (2) What is the expert consensus on how to resolve these complaints by adjusting hearing aid parameters? Hearing aid dispensers provided descriptors that impaired listeners use to describe their reactions to specific hearing aid fitting problems. Hearing aid fitting experts were asked "How would you adjust the hearing aid if its user reports that the aid sounds…?" with the blank filled with each of the 40 most frequently mentioned descriptors. 112 hearing aid dispensers and 15 hearing aid experts. The expert solution with the highest weight value was considered the best solution for that descriptor. Principal component analysis (PCA) was performed to identify a factor structure in fitting problems. Nine fitting problems could be identified resulting in an expert-based, hearing aid manufacturer independent, fine-tuning fitting assistant for clinical use. The construction of an expert-based, hearing aid manufacturer independent, fine-tuning fitting assistant to be used as an additional tool in the iterative fitting process is feasible.

NMF-Based Image Quality Assessment Using Extreme Learning Machine.

PubMed

Wang, Shuigen; Deng, Chenwei; Lin, Weisi; Huang, Guang-Bin; Zhao, Baojun

2017-01-01

Numerous state-of-the-art perceptual image quality assessment (IQA) algorithms share a common two-stage process: distortion description followed by distortion effects pooling. As for the first stage, the distortion descriptors or measurements are expected to be effective representatives of human visual variations, while the second stage should well express the relationship among quality descriptors and the perceptual visual quality. However, most of the existing quality descriptors (e.g., luminance, contrast, and gradient) do not seem to be consistent with human perception, and the effects pooling is often done in ad-hoc ways. In this paper, we propose a novel full-reference IQA metric. It applies non-negative matrix factorization (NMF) to measure image degradations by making use of the parts-based representation of NMF. On the other hand, a new machine learning technique [extreme learning machine (ELM)] is employed to address the limitations of the existing pooling techniques. Compared with neural networks and support vector regression, ELM can achieve higher learning accuracy with faster learning speed. Extensive experimental results demonstrate that the proposed metric has better performance and lower computational complexity in comparison with the relevant state-of-the-art approaches.

Local Multi-Grouped Binary Descriptor With Ring-Based Pooling Configuration and Optimization.

PubMed

Gao, Yongqiang; Huang, Weilin; Qiao, Yu

2015-12-01

Local binary descriptors are attracting increasingly attention due to their great advantages in computational speed, which are able to achieve real-time performance in numerous image/vision applications. Various methods have been proposed to learn data-dependent binary descriptors. However, most existing binary descriptors aim overly at computational simplicity at the expense of significant information loss which causes ambiguity in similarity measure using Hamming distance. In this paper, by considering multiple features might share complementary information, we present a novel local binary descriptor, referred as ring-based multi-grouped descriptor (RMGD), to successfully bridge the performance gap between current binary and floated-point descriptors. Our contributions are twofold. First, we introduce a new pooling configuration based on spatial ring-region sampling, allowing for involving binary tests on the full set of pairwise regions with different shapes, scales, and distances. This leads to a more meaningful description than the existing methods which normally apply a limited set of pooling configurations. Then, an extended Adaboost is proposed for an efficient bit selection by emphasizing high variance and low correlation, achieving a highly compact representation. Second, the RMGD is computed from multiple image properties where binary strings are extracted. We cast multi-grouped features integration as rankSVM or sparse support vector machine learning problem, so that different features can compensate strongly for each other, which is the key to discriminativeness and robustness. The performance of the RMGD was evaluated on a number of publicly available benchmarks, where the RMGD outperforms the state-of-the-art binary descriptors significantly.

RANZCR Body Systems Framework of diagnostic imaging examination descriptors.

PubMed

Pitman, Alexander G; Penlington, Lisa; Doromal, Darren; Slater, Gregory; Vukolova, Natalia

2014-08-01

A unified and logical system of descriptors for diagnostic imaging examinations and procedures is a desirable resource for radiology in Australia and New Zealand and is needed to support core activities of RANZCR. Existing descriptor systems available in Australia and New Zealand (including the Medicare DIST and the ACC Schedule) have significant limitations and are inappropriate for broader clinical application. An anatomically based grid was constructed, with anatomical structures arranged in rows and diagnostic imaging modalities arranged in columns (including nuclear medicine and positron emission tomography). The grid was segregated into five body systems. The cells at the intersection of an anatomical structure row and an imaging modality column were populated with short, formulaic descriptors of the applicable diagnostic imaging examinations. Clinically illogical or physically impossible combinations were 'greyed out'. Where the same examination applied to different anatomical structures, the descriptor was kept identical for the purposes of streamlining. The resulting Body Systems Framework of diagnostic imaging examination descriptors lists all the reasonably common diagnostic imaging examinations currently performed in Australia and New Zealand using a unified grid structure allowing navigation by both referrers and radiologists. The Framework has been placed on the RANZCR website and is available for access free of charge by registered users. The Body Systems Framework of diagnostic imaging examination descriptors is a system of descriptors based on relationships between anatomical structures and imaging modalities. The Framework is now available as a resource and reference point for the radiology profession and to support core College activities. © 2014 The Royal Australian and New Zealand College of Radiologists.

Improving virtual screening predictive accuracy of Human kallikrein 5 inhibitors using machine learning models.

PubMed

Fang, Xingang; Bagui, Sikha; Bagui, Subhash

2017-08-01

The readily available high throughput screening (HTS) data from the PubChem database provides an opportunity for mining of small molecules in a variety of biological systems using machine learning techniques. From the thousands of available molecular descriptors developed to encode useful chemical information representing the characteristics of molecules, descriptor selection is an essential step in building an optimal quantitative structural-activity relationship (QSAR) model. For the development of a systematic descriptor selection strategy, we need the understanding of the relationship between: (i) the descriptor selection; (ii) the choice of the machine learning model; and (iii) the characteristics of the target bio-molecule. In this work, we employed the Signature descriptor to generate a dataset on the Human kallikrein 5 (hK 5) inhibition confirmatory assay data and compared multiple classification models including logistic regression, support vector machine, random forest and k-nearest neighbor. Under optimal conditions, the logistic regression model provided extremely high overall accuracy (98%) and precision (90%), with good sensitivity (65%) in the cross validation test. In testing the primary HTS screening data with more than 200K molecular structures, the logistic regression model exhibited the capability of eliminating more than 99.9% of the inactive structures. As part of our exploration of the descriptor-model-target relationship, the excellent predictive performance of the combination of the Signature descriptor and the logistic regression model on the assay data of the Human kallikrein 5 (hK 5) target suggested a feasible descriptor/model selection strategy on similar targets. Copyright © 2017 Elsevier Ltd. All rights reserved.

Expanding Preschoolers' Use of Object Descriptions and Comparisons by Teaching "Category-Descriptor" Statements.

ERIC Educational Resources Information Center

Weisberg, Paul

2003-01-01

Six preschool children, mostly from poverty-level backgrounds, were taught to make descriptive statements about objects. The category-descriptor statements were organized and sequenced into four clusters. As sets of new statements were successively taught and evaluated, the number and diversity of probed category and descriptor terms steadily and…

Predicting membrane protein types by the LLDA algorithm.

PubMed

Wang, Tong; Yang, Jie; Shen, Hong-Bin; Chou, Kuo-Chen

2008-01-01

Membrane proteins are generally classified into the following eight types: (1) type I transmembrane, (2) type II, (3) type III, (4) type IV, (5) multipass transmembrane, (6) lipid-chain-anchored membrane, (7) GPI-anchored membrane, and (8) peripheral membrane (K.C. Chou and H.B. Shen: BBRC, 2007, 360: 339-345). Knowing the type of an uncharacterized membrane protein often provides useful clues for finding its biological function and interaction process with other molecules in a biological system. With the explosion of protein sequences generated in the Post-Genomic Age, it is urgent to develop an automated method to deal with such a challenge. Recently, the PsePSSM (Pseudo Position-Specific Score Matrix) descriptor is proposed by Chou and Shen (Biochem. Biophys. Res. Comm. 2007, 360, 339-345) to represent a protein sample. The advantage of the PsePSSM descriptor is that it can combine the evolution information and sequence-correlated information. However, incorporating all these effects into a descriptor may cause the "high dimension disaster". To overcome such a problem, the fusion approach was adopted by Chou and Shen. Here, a completely different approach, the so-called LLDA (Local Linear Discriminant Analysis) is introduced to extract the key features from the high-dimensional PsePSSM space. The dimension-reduced descriptor vector thus obtained is a compact representation of the original high dimensional vector. Our jackknife and independent dataset test results indicate that it is very promising to use the LLDA approach to cope with complicated problems in biological systems, such as predicting the membrane protein type.

Odor-color associations differ with verbal descriptors for odors: A comparison of three linguistically diverse groups.

PubMed

de Valk, Josje M; Wnuk, Ewelina; Huisman, John L A; Majid, Asifa

2017-08-01

People appear to have systematic associations between odors and colors. Previous research has emphasized the perceptual nature of these associations, but little attention has been paid to what role language might play. It is possible odor-color associations arise through a process of labeling; that is, participants select a descriptor for an odor and then choose a color accordingly (e.g., banana odor → "banana" label → yellow). If correct, this would predict odor-color associations would differ as odor descriptions differ. We compared speakers of Dutch (who overwhelmingly describe odors by referring to the source; e.g., smells like banana) with speakers of Maniq and Thai (who also describe odors with dedicated, abstract smell vocabulary; e.g., musty), and tested whether the type of descriptor mattered for odor-color associations. Participants were asked to select a color that they associated with an odor on two separate occasions (to test for consistency), and finally to label the odors. We found the hunter-gatherer Maniq showed few, if any, consistent or accurate odor-color associations. More importantly, we found the types of descriptors used to name the smells were related to the odor-color associations. When people used abstract smell terms to describe odors, they were less likely to choose a color match, but when they described an odor with a source-based term, their color choices more accurately reflected the odor source, particularly when the odor source was named correctly (e.g., banana odor → yellow). This suggests language is an important factor in odor-color cross-modal associations.

Texture classification using non-Euclidean Minkowski dilation

NASA Astrophysics Data System (ADS)

Florindo, Joao B.; Bruno, Odemir M.

2018-03-01

This study presents a new method to extract meaningful descriptors of gray-scale texture images using Minkowski morphological dilation based on the Lp metric. The proposed approach is motivated by the success previously achieved by Bouligand-Minkowski fractal descriptors on texture classification. In essence, such descriptors are directly derived from the morphological dilation of a three-dimensional representation of the gray-level pixels using the classical Euclidean metric. In this way, we generalize the dilation for different values of p in the Lp metric (Euclidean is a particular case when p = 2) and obtain the descriptors from the cumulated distribution of the distance transform computed over the texture image. The proposed method is compared to other state-of-the-art approaches (such as local binary patterns and textons for example) in the classification of two benchmark data sets (UIUC and Outex). The proposed descriptors outperformed all the other approaches in terms of rate of images correctly classified. The interesting results suggest the potential of these descriptors in this type of task, with a wide range of possible applications to real-world problems.

Flavoured cigarettes, sensation seeking and adolescents' perceptions of cigarette brands.

PubMed

Manning, K C; Kelly, K J; Comello, M L

2009-12-01

This study examined the interactive effects of cigarette package flavour descriptors and sensation seeking on adolescents' brand perceptions. High school students (n = 253) were randomly assigned to one of two experimental conditions and sequentially exposed to cigarette package illustrations for three different brands. In the flavour descriptor condition, the packages included a description of the cigarettes as "cherry", while in the traditional descriptor condition the cigarette brands were described with common phrases found on tobacco packages such as "domestic blend." Following exposure to each package participants' hedonic beliefs, brand attitudes and trial intentions were assessed. Sensation seeking was also measured, and participants were categorised as lower or higher sensation seekers. Across hedonic belief, brand attitude and trial intention measures, there were interactions between package descriptor condition and sensation seeking. These interactions revealed that among high (but not low) sensation seekers, exposure to cigarette packages including sweet flavour descriptors led to more favourable brand impressions than did exposure to packages with traditional descriptors. Among high sensation seeking youths, the appeal of cigarette brands is enhanced through the use of flavours and associated descriptions on product packaging.

A Quantum Chemical and Statistical Study of Phenolic Schiff Bases with Antioxidant Activity against DPPH Free Radical

PubMed Central

Anouar, El Hassane

2014-01-01

Phenolic Schiff bases are known as powerful antioxidants. To select the electronic, 2D and 3D descriptors responsible for the free radical scavenging ability of a series of 30 phenolic Schiff bases, a set of molecular descriptors were calculated by using B3P86 (Becke’s three parameter hybrid functional with Perdew 86 correlation functional) combined with 6-31 + G(d,p) basis set (i.e., at the B3P86/6-31 + G(d,p) level of theory). The chemometric methods, simple and multiple linear regressions (SLR and MLR), principal component analysis (PCA) and hierarchical cluster analysis (HCA) were employed to reduce the dimensionality and to investigate the relationship between the calculated descriptors and the antioxidant activity. The results showed that the antioxidant activity mainly depends on the first and second bond dissociation enthalpies of phenolic hydroxyl groups, the dipole moment and the hydrophobicity descriptors. The antioxidant activity is inversely proportional to the main descriptors. The selected descriptors discriminate the Schiff bases into active and inactive antioxidants. PMID:26784873

An Effective 3D Shape Descriptor for Object Recognition with RGB-D Sensors

PubMed Central

Liu, Zhong; Zhao, Changchen; Wu, Xingming; Chen, Weihai

2017-01-01

RGB-D sensors have been widely used in various areas of computer vision and graphics. A good descriptor will effectively improve the performance of operation. This article further analyzes the recognition performance of shape features extracted from multi-modality source data using RGB-D sensors. A hybrid shape descriptor is proposed as a representation of objects for recognition. We first extracted five 2D shape features from contour-based images and five 3D shape features over point cloud data to capture the global and local shape characteristics of an object. The recognition performance was tested for category recognition and instance recognition. Experimental results show that the proposed shape descriptor outperforms several common global-to-global shape descriptors and is comparable to some partial-to-global shape descriptors that achieved the best accuracies in category and instance recognition. Contribution of partial features and computational complexity were also analyzed. The results indicate that the proposed shape features are strong cues for object recognition and can be combined with other features to boost accuracy. PMID:28245553

Bayesian screening for active compounds in high-dimensional chemical spaces combining property descriptors and molecular fingerprints.

PubMed

Vogt, Martin; Bajorath, Jürgen

2008-01-01

Bayesian classifiers are increasingly being used to distinguish active from inactive compounds and search large databases for novel active molecules. We introduce an approach to directly combine the contributions of property descriptors and molecular fingerprints in the search for active compounds that is based on a Bayesian framework. Conventionally, property descriptors and fingerprints are used as alternative features for virtual screening methods. Following the approach introduced here, probability distributions of descriptor values and fingerprint bit settings are calculated for active and database molecules and the divergence between the resulting combined distributions is determined as a measure of biological activity. In test calculations on a large number of compound activity classes, this methodology was found to consistently perform better than similarity searching using fingerprints and multiple reference compounds or Bayesian screening calculations using probability distributions calculated only from property descriptors. These findings demonstrate that there is considerable synergy between different types of property descriptors and fingerprints in recognizing diverse structure-activity relationships, at least in the context of Bayesian modeling.

Prediction of olive oil sensory descriptors using instrumental data fusion and partial least squares (PLS) regression.

PubMed

Borràs, Eva; Ferré, Joan; Boqué, Ricard; Mestres, Montserrat; Aceña, Laura; Calvo, Angels; Busto, Olga

2016-08-01

Headspace-Mass Spectrometry (HS-MS), Fourier Transform Mid-Infrared spectroscopy (FT-MIR) and UV-Visible spectrophotometry (UV-vis) instrumental responses have been combined to predict virgin olive oil sensory descriptors. 343 olive oil samples analyzed during four consecutive harvests (2010-2014) were used to build multivariate calibration models using partial least squares (PLS) regression. The reference values of the sensory attributes were provided by expert assessors from an official taste panel. The instrumental data were modeled individually and also using data fusion approaches. The use of fused data with both low- and mid-level of abstraction improved PLS predictions for all the olive oil descriptors. The best PLS models were obtained for two positive attributes (fruity and bitter) and two defective descriptors (fusty and musty), all of them using data fusion of MS and MIR spectral fingerprints. Although good predictions were not obtained for some sensory descriptors, the results are encouraging, specially considering that the legal categorization of virgin olive oils only requires the determination of fruity and defective descriptors. Copyright © 2016 Elsevier B.V. All rights reserved.

Characterizing region of interest in image using MPEG-7 visual descriptors

NASA Astrophysics Data System (ADS)

Ryu, Min-Sung; Park, Soo-Jun; Won, Chee Sun

2005-08-01

In this paper, we propose a region-based image retrieval system using EHD (Edge Histogram Descriptor) and CLD (Color Layout Descriptor) of MPEG-7 descriptors. The combined descriptor can efficiently describe edge and color features in terms of sub-image regions. That is, the basic unit for the selection of the region-of-interest (ROI) in the image is the sub-image block of the EHD, which corresponds to 16 (i.e., 4x4) non-overlapping image blocks in the image space. This implies that, to have a one-to-one region correspondence between EHD and CLD, we need to take an 8x8 inverse DCT (IDCT) for the CLD. Experimental results show that the proposed retrieval scheme can be used for image retrieval with the ROI based image retrieval for MPEG-7 indexed images.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Singh, Kunwar P., E-mail: kpsingh_52@yahoo.com; Gupta, Shikha

Ensemble learning approach based decision treeboost (DTB) and decision tree forest (DTF) models are introduced in order to establish quantitative structure–toxicity relationship (QSTR) for the prediction of toxicity of 1450 diverse chemicals. Eight non-quantum mechanical molecular descriptors were derived. Structural diversity of the chemicals was evaluated using Tanimoto similarity index. Stochastic gradient boosting and bagging algorithms supplemented DTB and DTF models were constructed for classification and function optimization problems using the toxicity end-point in T. pyriformis. Special attention was drawn to prediction ability and robustness of the models, investigated both in external and 10-fold cross validation processes. In complete data,more » optimal DTB and DTF models rendered accuracies of 98.90%, 98.83% in two-category and 98.14%, 98.14% in four-category toxicity classifications. Both the models further yielded classification accuracies of 100% in external toxicity data of T. pyriformis. The constructed regression models (DTB and DTF) using five descriptors yielded correlation coefficients (R{sup 2}) of 0.945, 0.944 between the measured and predicted toxicities with mean squared errors (MSEs) of 0.059, and 0.064 in complete T. pyriformis data. The T. pyriformis regression models (DTB and DTF) applied to the external toxicity data sets yielded R{sup 2} and MSE values of 0.637, 0.655; 0.534, 0.507 (marine bacteria) and 0.741, 0.691; 0.155, 0.173 (algae). The results suggest for wide applicability of the inter-species models in predicting toxicity of new chemicals for regulatory purposes. These approaches provide useful strategy and robust tools in the screening of ecotoxicological risk or environmental hazard potential of chemicals. - Graphical abstract: Importance of input variables in DTB and DTF classification models for (a) two-category, and (b) four-category toxicity intervals in T. pyriformis data. Generalization and predictive abilities of the constructed (c) DTB and (d) DTF regression models to predict the T. pyriformis toxicity of diverse chemicals. - Highlights: • Ensemble learning (EL) based models constructed for toxicity prediction of chemicals • Predictive models used a few simple non-quantum mechanical molecular descriptors. • EL-based DTB/DTF models successfully discriminated toxic and non-toxic chemicals. • DTB/DTF regression models precisely predicted toxicity of chemicals in multi-species. • Proposed EL based models can be used as tool to predict toxicity of new chemicals.« less

Implementing the European Marine Strategy Framework Directive: Scientific challenges and opportunities

NASA Astrophysics Data System (ADS)

Newton, Alice; Borja, Angel; Solidoro, Cosimo; Grégoire, Marilaure

2015-10-01

The Marine Strategy Framework Directive (MSFD; EC, 2008) is an ambitious European policy instrument that aims to achieve Good Environmental Status (GES) in the 5,720,000 km2 of European seas by 2020, using an Ecosystem Approach. GES is to be assessed using 11 descriptors and up to 56 indicators (European Commission, 2010), and the goal is for clean, healthy and productive seas that are the basis for marine-based development, known as Blue-Growth. The MSFD is one of many policy instruments, such as the Water Framework Directive, the Common Fisheries Policy and the Habitats Directive that, together, should result in "Healthy Oceans and Productive Ecosystems - HOPE". Researchers working together with stakeholders such as the Member States environmental agencies, the European Environmental Agency, and the Regional Sea Conventions, are to provide the scientific knowledge basis for the implementation of the MSFD. This represents both a fascinating challenge and a stimulating opportunity.

MMPI-2 validity, clinical and content scales, and the Fake Bad Scale for personal injury litigants claiming idiopathic environmental intolerance.

PubMed

Staudenmayer, Herman; Phillips, Scott

2007-01-01

Idiopathic environmental intolerance (IEI) is a descriptor for nonspecific complaints that are attributed to environmental exposure. The Minnesota Multiphasic Personality Inventory 2 (MMPI-2) was administered to 50 female and 20 male personal injury litigants alleging IEI. The validity scales indicated no overreporting of psychopathology. Half of the cases had elevated scores on validity scales suggesting defensiveness, and a large number had elevations on Fake Bad Scale (FBS) suggesting overreporting of unauthenticated symptoms. The average T-score profile for females was defined by the two-point code type 3-1 (Hysteria-Hypochondriasis), and the average T-score profile for males was defined by the three-point code type 3-1-2 (Hysteria, Hypochondriasis-Depression). On the content scales, Health Concerns (HEA) scale was significantly elevated. Idiopathic environmental intolerance litigants (a) are more defensive about expressing psychopathology, (b) express distress through somatization, (c) use a self-serving misrepresentation of exaggerated health concerns, and (d) may exaggerate unauthenticated symptoms suggesting malingering.

Vibration mode shape recognition using image processing

NASA Astrophysics Data System (ADS)

Wang, Weizhuo; Mottershead, John E.; Mares, Cristinel

2009-10-01

Currently the most widely used method for comparing mode shapes from finite elements and experimental measurements is the modal assurance criterion (MAC), which can be interpreted as the cosine of the angle between the numerical and measured eigenvectors. However, the eigenvectors only contain the displacement of discrete coordinates, so that the MAC index carries no explicit information on shape features. New techniques, based upon the well-developed philosophies of image processing (IP) and pattern recognition (PR) are considered in this paper. The Zernike moment descriptor (ZMD), Fourier descriptor (FD), and wavelet descriptor (WD) are the most popular shape descriptors due to their outstanding properties in IP and PR. These include (1) for the ZMD-rotational invariance, expression and computing efficiency, ease of reconstruction and robustness to noise; (2) for the FD—separation of the global shape and shape-details by low and high frequency components, respectively, invariance under geometric transformation; (3) for the WD—multi-scale representation and local feature detection. Once a shape descriptor has been adopted, the comparison of mode shapes is transformed to a comparison of multidimensional shape feature vectors. Deterministic and statistical methods are presented. The deterministic problem of measuring the degree of similarity between two mode shapes (possibly one from a vibration test and the other from a finite element model) may be carried out using Pearson's correlation. Similar shape feature vectors may be arranged in clusters separated by Euclidian distances in the feature space. In the statistical analysis we are typically concerned with the classification of a test mode shape according to clusters of shape feature vectors obtained from a randomised finite element model. The dimension of the statistical problem may often be reduced by principal component analysis. Then, in addition to the Euclidian distance, the Mahalanobis distance, defining the separation of the test point from the cluster in terms of its standard deviation, becomes an important measure. Bayesian decision theory may be applied to formally minimise the risk of misclassification of the test shape feature vector. In this paper the ZMD is applied to the problem of mode shape recognition for a circular plate. Results show that the ZMD has considerable advantages over the traditional MAC index when identifying the cyclically symmetric mode shapes that occur in axisymmetric structures at identical frequencies. Mode shape recognition of rectangular plates is carried out by the FD. Also, the WD is applied to the problem of recognising the mode shapes in the thin and thick regions of a plate with different thicknesses. It shows the benefit of using the WD to identify mode-shapes having both local and global components. The comparison and classification of mode shapes using IP and PR provides a 'toolkit' to complement the conventional MAC approach. The selection of a particular shape descriptor and classification method will depend upon the problem in hand and the experience of the analyst.

Shuffling cross-validation-bee algorithm as a new descriptor selection method for retention studies of pesticides in biopartitioning micellar chromatography.

PubMed

Zarei, Kobra; Atabati, Morteza; Ahmadi, Monire

2017-05-04

Bee algorithm (BA) is an optimization algorithm inspired by the natural foraging behaviour of honey bees to find the optimal solution which can be proposed to feature selection. In this paper, shuffling cross-validation-BA (CV-BA) was applied to select the best descriptors that could describe the retention factor (log k) in the biopartitioning micellar chromatography (BMC) of 79 heterogeneous pesticides. Six descriptors were obtained using BA and then the selected descriptors were applied for model development using multiple linear regression (MLR). The descriptor selection was also performed using stepwise, genetic algorithm and simulated annealing methods and MLR was applied to model development and then the results were compared with those obtained from shuffling CV-BA. The results showed that shuffling CV-BA can be applied as a powerful descriptor selection method. Support vector machine (SVM) was also applied for model development using six selected descriptors by BA. The obtained statistical results using SVM were better than those obtained using MLR, as the root mean square error (RMSE) and correlation coefficient (R) for whole data set (training and test), using shuffling CV-BA-MLR, were obtained as 0.1863 and 0.9426, respectively, while these amounts for the shuffling CV-BA-SVM method were obtained as 0.0704 and 0.9922, respectively.

3D Riesz-wavelet based Covariance descriptors for texture classification of lung nodule tissue in CT.

PubMed

Cirujeda, Pol; Muller, Henning; Rubin, Daniel; Aguilera, Todd A; Loo, Billy W; Diehn, Maximilian; Binefa, Xavier; Depeursinge, Adrien

2015-01-01

In this paper we present a novel technique for characterizing and classifying 3D textured volumes belonging to different lung tissue types in 3D CT images. We build a volume-based 3D descriptor, robust to changes of size, rigid spatial transformations and texture variability, thanks to the integration of Riesz-wavelet features within a Covariance-based descriptor formulation. 3D Riesz features characterize the morphology of tissue density due to their response to changes in intensity in CT images. These features are encoded in a Covariance-based descriptor formulation: this provides a compact and flexible representation thanks to the use of feature variations rather than dense features themselves and adds robustness to spatial changes. Furthermore, the particular symmetric definite positive matrix form of these descriptors causes them to lay in a Riemannian manifold. Thus, descriptors can be compared with analytical measures, and accurate techniques from machine learning and clustering can be adapted to their spatial domain. Additionally we present a classification model following a "Bag of Covariance Descriptors" paradigm in order to distinguish three different nodule tissue types in CT: solid, ground-glass opacity, and healthy lung. The method is evaluated on top of an acquired dataset of 95 patients with manually delineated ground truth by radiation oncology specialists in 3D, and quantitative sensitivity and specificity values are presented.

Using the product threshold model for estimating separately the effect of temperature on male and female fertility.

PubMed

Tusell, L; David, I; Bodin, L; Legarra, A; Rafel, O; López-Bejar, M; Piles, M

2011-12-01

Animals under environmental thermal stress conditions have reduced fertility due to impairment of some mechanisms involved in their reproductive performance that are different in males and females. As a consequence, the most sensitive periods of time and the magnitude of effect of temperature on fertility can differ between sexes. The objective of this study was to estimate separately the effect of temperature in different periods around the insemination time on male and on female fertility by using the product threshold model. This model assumes that an observed reproduction outcome is the result of the product of 2 unobserved variables corresponding to the unobserved fertilities of the 2 individuals involved in the mating. A total of 7,625 AI records from rabbits belonging to a line selected for growth rate and indoor daily temperature records were used. The average maximum daily temperature and the proportion of days in which the maximum temperature was greater than 25°C were used as temperature descriptors. These descriptors were calculated for several periods around the day of AI. In the case of males, 4 periods of time covered different stages of the spermatogenesis, the transit through the epididymus of the sperm, and the day of AI. For females, 5 periods of time covered the phases of preovulatory follicular maturation including day of AI and ovulation, fertilization and peri-implantational stage of the embryos, embryonic and early fetal periods of gestation, and finally, late gestation until birth. The effect of the different temperature descriptors was estimated in the corresponding male and female liabilities in a set of threshold product models. The temperature of the day of AI seems to be the most relevant temperature descriptor affecting male fertility because greater temperature records on the day of AI caused a decrease in male fertility (-6% in male fertility rate with respect to thermoneutrality). Departures from the thermal zone in temperature descriptors covering several periods before AI until early gestation had a negative effect on female fertility, with the pre- and peri-implantational period of the embryos being especially sensitive (from -5 to -6% in female fertility rate with respect to thermoneutrality). The latest period of gestation was unaffected by the temperature. Overall, magnitude and persistency of the temperatures reached in the conditions of this study do not seem to be great enough to have a large effect on male and female rabbit fertility.

A macrophysical life cycle description for precipitating systems

NASA Astrophysics Data System (ADS)

Evaristo, Raquel; Xie, Xinxin; Troemel, Silke; Diederich, Malte; Simon, Juergen; Simmer, Clemens

2014-05-01

The lack of understanding of cloud and precipitation processes is still the overarching problem of climate simulation, and prediction. The work presented is part of the HD(CP)2 project (High Definition Clouds and Precipitation for Advancing Climate Predictions) which aims at building a very high resolution model in order to evaluate and exploit regional hindcasts for the purpose of parameterization development. To this end, an observational object-based climatology for precipitation systems will be built, and shall later be compared with a twin model-based climatological data base for pseudo precipitation events within an event-based model validation approach. This is done by identifying internal structures, described by means of macrophysical descriptors used to characterize the temporal development of tracked rain events. 2 pre-requisites are necessary for this: 1) a tracking algorithm, and 2) 3D radar/satellite composite. Both prerequisites are ready to be used, and have already been applied to a few case studies. Some examples of these macrophysical descriptors are differential reflectivity columns, bright band fraction and trend, cloud top heights, the spatial extent of updrafts or downdrafts or the ice content. We will show one case study from August 5th 2012, when convective precipitation was observed simultaneously by the BOXPOL and JUXPOL X-band polarimetric radars. We will follow the main paths identified by the tracking algorithm during this event and identify in the 3D composite the descriptors that characterize precipitation development, their temporal evolution, and the different macrophysical processes that are ultimately related to the precipitation observed. In a later stage these observations will be compared to the results of hydrometeor classification algorithm, in order to link the macrophysical and microphysical aspects of the storm evolution. The detailed microphysical processes are the subject of a closely related work also presented in this session: Microphysical processes observed by X band polarimetric radars during the evolution of storm systems, by Xinxin Xie et al.

Developing Illustrative Descriptors of Aspects of Mediation for the Common European Framework of Reference (CEFR): A Council of Europe Project

ERIC Educational Resources Information Center

North, Brian; Piccardo, Enrica

2016-01-01

The notion of mediation has been the object of growing interest in second language education in recent years. The increasing awareness of the complex nature of the process of learning--and teaching--stretches our collective reflection towards less explored areas. In mediation, the immediate focus is on the role of language in processes like…

Nutrition and prevention of chronic diseases: a unifying eco-nutritional strategy.

PubMed

Wahlqvist, M L

2004-02-01

Increasing efforts are being made to address, in public health policy (PHP), both the persistence of nutritional deprivation in economically disadvantaged communities, and the increase in so-called "chronic disease" (abdominal obesity, diabetes, cardiovascular disease, certain cancers, osteoporosis, arthritides, and inflammatory disease) in communities at all stages of economic development. The problems in the "chronic disease" descriptor are that its origins may be as early as conception, rather than during the postnatal lifespan, or even in previous generations; it may appear abruptly or slowly; and it may be amenable to environmental and behavioural intervention well into its course and in older age groups. It is also not necessarily "non-communicable", a qualifier often used for "chronic disease" (chronic non-communicable disease or CNCD) and often has inflammatory features, for example the inflammatory marker C-reactive protein is a predictor of macrovascular disease and ischaemic events can, in part, be prevented in the affected by influenzal vaccination. The nexus between immunodeficiency, inflammatory processes and nutritional status which is characteristic of "infective" and food-borne illness, is also more and more evident in "chronic disease". It may be more helpful to consider "chronic disease" as "eco-disease" with its environmental and behavioural contributors, and to regard that which is clearly nutritionally dependent as "eco-nutritional disease".

Characterisation of physical environmental factors on an intertidal sandflat, Manukau Harbour, New Zealand

USGS Publications Warehouse

Bell, R.G.; Hume, T.M.; Dolphin, T.J.; Green, M.O.; Walters, R.A.

1997-01-01

Physical environmental factors, including sediment characteristics, inundation time, tidal currents and wind waves, likely to influence the structure of the benthic community at meso-scales (1-100 m) were characterised for a sandflat off Wiroa Island (Manukau Harbour, New Zealand). In a 500 x 250 m study site, sediment characteristics and bed topography were mostly homogenous apart from patches of low-relief ridges and runnels. Field measurements and hydrodynamic modelling portray a complex picture of sediment or particulate transport on the intertidal flat, involving interactions between the larger scale tidal processes and the smaller scale wave dynamics (1-4 s; 1-15 m). Peak tidal currents in isolation are incapable of eroding bottom sediments, but in combination with near-bed orbital currents generated by only very small wind waves, sediment transport can be initiated. Work done on the bed integrated over an entire tidal cycle by prevailing wind waves is greatest on the elevated and flatter slopes of the study site, where waves shoal over a wider surf zone and water depths remain shallow e enough for wave-orbital currents to disturb the bed. The study also provided physical descriptors quantifying static and hydrodynamic (tidal and wave) factors which were used in companion studies on ecological spatial modelling of bivalve distributions and micro-scale sediment reworking and transport.

Global quantitative indices reflecting provider process-of-care: data-base derivation.

PubMed

Moran, John L; Solomon, Patricia J

2010-04-19

Controversy has attended the relationship between risk-adjusted mortality and process-of-care. There would be advantage in the establishment, at the data-base level, of global quantitative indices subsuming the diversity of process-of-care. A retrospective, cohort study of patients identified in the Australian and New Zealand Intensive Care Society Adult Patient Database, 1993-2003, at the level of geographic and ICU-level descriptors (n = 35), for both hospital survivors and non-survivors. Process-of-care indices were established by analysis of: (i) the smoothed time-hazard curve of individual patient discharge and determined by pharmaco-kinetic methods as area under the hazard-curve (AUC), reflecting the integrated experience of the discharge process, and time-to-peak-hazard (TMAX, in days), reflecting the time to maximum rate of hospital discharge; and (ii) individual patient ability to optimize output (as length-of-stay) for recorded data-base physiological inputs; estimated as a technical production-efficiency (TE, scaled [0,(maximum)1]), via the econometric technique of stochastic frontier analysis. For each descriptor, multivariate correlation-relationships between indices and summed mortality probability were determined. The data-set consisted of 223129 patients from 99 ICUs with mean (SD) age and APACHE III score of 59.2(18.9) years and 52.7(30.6) respectively; 41.7% were female and 45.7% were mechanically ventilated within the first 24 hours post-admission. For survivors, AUC was maximal in rural and for-profit ICUs, whereas TMAX (>or= 7.8 days) and TE (>or= 0.74) were maximal in tertiary-ICUs. For non-survivors, AUC was maximal in tertiary-ICUs, but TMAX (>or= 4.2 days) and TE (>or= 0.69) were maximal in for-profit ICUs. Across descriptors, significant differences in indices were demonstrated (analysis-of-variance, P

Discovering collectively informative descriptors from high-throughput experiments

PubMed Central

2009-01-01

Background Improvements in high-throughput technology and its increasing use have led to the generation of many highly complex datasets that often address similar biological questions. Combining information from these studies can increase the reliability and generalizability of results and also yield new insights that guide future research. Results This paper describes a novel algorithm called BLANKET for symmetric analysis of two experiments that assess informativeness of descriptors. The experiments are required to be related only in that their descriptor sets intersect substantially and their definitions of case and control are consistent. From resulting lists of n descriptors ranked by informativeness, BLANKET determines shortlists of descriptors from each experiment, generally of different lengths p and q. For any pair of shortlists, four numbers are evident: the number of descriptors appearing in both shortlists, in exactly one shortlist, or in neither shortlist. From the associated contingency table, BLANKET computes Right Fisher Exact Test (RFET) values used as scores over a plane of possible pairs of shortlist lengths [1,2]. BLANKET then chooses a pair or pairs with RFET score less than a threshold; the threshold depends upon n and shortlist length limits and represents a quality of intersection achieved by less than 5% of random lists. Conclusions Researchers seek within a universe of descriptors some minimal subset that collectively and efficiently predicts experimental outcomes. Ideally, any smaller subset should be insufficient for reliable prediction and any larger subset should have little additional accuracy. As a method, BLANKET is easy to conceptualize and presents only moderate computational complexity. Many existing databases could be mined using BLANKET to suggest optimal sets of predictive descriptors. PMID:20021653

Universal fragment descriptors for predicting properties of inorganic crystals

NASA Astrophysics Data System (ADS)

Isayev, Olexandr; Oses, Corey; Toher, Cormac; Gossett, Eric; Curtarolo, Stefano; Tropsha, Alexander

2017-06-01

Although historically materials discovery has been driven by a laborious trial-and-error process, knowledge-driven materials design can now be enabled by the rational combination of Machine Learning methods and materials databases. Here, data from the AFLOW repository for ab initio calculations is combined with Quantitative Materials Structure-Property Relationship models to predict important properties: metal/insulator classification, band gap energy, bulk/shear moduli, Debye temperature and heat capacities. The prediction's accuracy compares well with the quality of the training data for virtually any stoichiometric inorganic crystalline material, reciprocating the available thermomechanical experimental data. The universality of the approach is attributed to the construction of the descriptors: Property-Labelled Materials Fragments. The representations require only minimal structural input allowing straightforward implementations of simple heuristic design rules.

Blurred image recognition by legendre moment invariants

PubMed Central

Zhang, Hui; Shu, Huazhong; Han, Guo-Niu; Coatrieux, Gouenou; Luo, Limin; Coatrieux, Jean-Louis

2010-01-01

Processing blurred images is a key problem in many image applications. Existing methods to obtain blur invariants which are invariant with respect to centrally symmetric blur are based on geometric moments or complex moments. In this paper, we propose a new method to construct a set of blur invariants using the orthogonal Legendre moments. Some important properties of Legendre moments for the blurred image are presented and proved. The performance of the proposed descriptors is evaluated with various point-spread functions and different image noises. The comparison of the present approach with previous methods in terms of pattern recognition accuracy is also provided. The experimental results show that the proposed descriptors are more robust to noise and have better discriminative power than the methods based on geometric or complex moments. PMID:19933003

Universal fragment descriptors for predicting properties of inorganic crystals.

PubMed

Isayev, Olexandr; Oses, Corey; Toher, Cormac; Gossett, Eric; Curtarolo, Stefano; Tropsha, Alexander

2017-06-05

Although historically materials discovery has been driven by a laborious trial-and-error process, knowledge-driven materials design can now be enabled by the rational combination of Machine Learning methods and materials databases. Here, data from the AFLOW repository for ab initio calculations is combined with Quantitative Materials Structure-Property Relationship models to predict important properties: metal/insulator classification, band gap energy, bulk/shear moduli, Debye temperature and heat capacities. The prediction's accuracy compares well with the quality of the training data for virtually any stoichiometric inorganic crystalline material, reciprocating the available thermomechanical experimental data. The universality of the approach is attributed to the construction of the descriptors: Property-Labelled Materials Fragments. The representations require only minimal structural input allowing straightforward implementations of simple heuristic design rules.

Environmental engineering education: examples of accreditation and quality assurance

NASA Astrophysics Data System (ADS)

Caporali, E.; Catelani, M.; Manfrida, G.; Valdiserri, J.

2013-12-01

Environmental engineers respond to the challenges posed by a growing population, intensifying land-use pressures, natural resources exploitation as well as rapidly evolving technology. The environmental engineer must develop technically sound solutions within the framework of maintaining or improving environmental quality, complying with public policy, and optimizing the utilization of resources. The engineer provides system and component design, serves as a technical advisor in policy making and legal deliberations, develops management schemes for resources, and provides technical evaluations of systems. Through the current work of environmental engineers, individuals and businesses are able to understand how to coordinate society's interaction with the environment. There will always be a need for engineers who are able to integrate the latest technologies into systems to respond to the needs for food and energy while protecting natural resources. In general, the environment-related challenges and problems need to be faced at global level, leading to the globalization of the engineering profession which requires not only the capacity to communicate in a common technical language, but also the assurance of an adequate and common level of technical competences, knowledge and understanding. In this framework, the Europe-based EUR ACE (European Accreditation of Engineering Programmes) system, currently operated by ENAEE - European Network for Accreditation of Engineering Education can represent the proper framework and accreditation system in order to provide a set of measures to assess the quality of engineering degree programmes in Europe and abroad. The application of the accreditation model EUR-ACE, and of the National Italian Degree Courses Accreditation System, promoted by the Italian National Agency for the Evaluation of Universities and Research Institutes (ANVUR), to the Environmental Engineering Degree Courses at the University of Firenze is presented. In particular, the accreditation models of the multidisciplinary first cycle degree in Civil, Building and Environmental Engineering and the more specific second cycle degree in Environmental Engineering are discussed. The critical issues to assure the quality and the status of environmental engineering graduates, in terms of applying knowledge capacities and technical innovative competences, according to the more engineering focused EUR-ACE skill descriptors as well as with respect to the Dublin descriptors, at local and global scale are also compared. The involvement of the professional working world in the definition of goals in skills, of typical expectations of achievements and abilities is also described. The system for educating engineers in communicating knowledge and understanding, making informed judgments and choices, capacities to lifelong learning is in addition assessed. The promotion of innovative aspects related with the environmental engineering education, and of the role that science and technology could play in environmental engineering education is also taken into consideration.

Direct memory access transfer completion notification

DOEpatents

Archer, Charles J [Rochester, MN; Blocksome, Michael A [Rochester, MN; Parker, Jeffrey J [Rochester, MN

2011-02-15

DMA transfer completion notification includes: inserting, by an origin DMA engine on an origin node in an injection first-in-first-out (`FIFO`) buffer, a data descriptor for an application message to be transferred to a target node on behalf of an application on the origin node; inserting, by the origin DMA engine, a completion notification descriptor in the injection FIFO buffer after the data descriptor for the message, the completion notification descriptor specifying a packet header for a completion notification packet; transferring, by the origin DMA engine to the target node, the message in dependence upon the data descriptor; sending, by the origin DMA engine, the completion notification packet to a local reception FIFO buffer using a local memory FIFO transfer operation; and notifying, by the origin DMA engine, the application that transfer of the message is complete in response to receiving the completion notification packet in the local reception FIFO buffer.

Direct memory access transfer completion notification

DOEpatents

Archer, Charles J.; Blocksome, Michael A.; Parker, Jeffrey J.

2010-08-17

Methods, apparatus, and products are disclosed for DMA transfer completion notification that include: inserting, by an origin DMA engine on an origin compute node in an injection FIFO buffer, a data descriptor for an application message to be transferred to a target compute node on behalf of an application on the origin compute node; inserting, by the origin DMA engine, a completion notification descriptor in the injection FIFO buffer after the data descriptor for the message, the completion notification descriptor specifying an address of a completion notification field in application storage for the application; transferring, by the origin DMA engine to the target compute node, the message in dependence upon the data descriptor; and notifying, by the origin DMA engine, the application that the transfer of the message is complete, including performing a local direct put operation to store predesignated notification data at the address of the completion notification field.

GIS based procedure of cumulative environmental impact assessment.

PubMed

Balakrishna Reddy, M; Blah, Baiantimon

2009-07-01

Scale and spatial limits of impact assessment study in a GIS platform are two very important factors that could have a bearing on the genuineness and quality of impact assessment. While effect of scale has been documented and well understood, no significant study has been carried out on spatial considerations in an impact assessment study employing GIS technique. A novel technique of impact assessment demonstrable through GIS approach termed hereby as 'spatial data integrated GIS impact assessment method (SGIAM)' is narrated in this paper. The technique makes a fundamental presumption that the importance of environmental impacts is dependent, among other things, on spatial distribution of the effects of the proposed action and of the affected receptors in a study area. For each environmental component considered (e.g., air quality), impact indices are calculated through aggregation of impact indicators which are measures of the severity of the impact. The presence and spread of environmental descriptors are suitably quantified through modeling techniques and depicted. The environmental impact index is calculated from data exported from ArcINFO, thus giving significant importance to spatial data in the impact assessment exercise.

Predicted Hematologic and Plasma Volume Responses Following Rapid Ascent to Progressive Altitudes

DTIC Science & Technology

2014-06-01

of these changes, and define baseline demographics and physiologic descriptors that are important in predicting these changes. The overall impact of... physiologic descriptors that are important in predicting these changes. Using general linear mixed models and a comprehensive relational database...accomplished using a comprehensive relational database containing individual ascent profiles, demographics, and physiologic subject descriptors as well as

CINAHL and MEDLINE: a comparison of indexing practices.

PubMed

Brenner, S H; McKinin, E J

1989-10-01

A random sample of fifty nursing articles indexed in both MEDLINE and CINAHL (NURSING & ALLIED HEALTH) during 1986 was used for comparing indexing practices. Indexing was analyzed by counting the number of major descriptors, the number of major and minor descriptors, the number of indexing access points, the number of common indexing access points, and the number and type of unique indexing access points. The study results indicate: there are few differences in the number of major descriptors used, MEDLINE uses almost twice as many descriptors, MEDLINE has almost twice as many indexing access points, and MEDLINE and CINAHL provide few common access points.

CINAHL and MEDLINE: a comparison of indexing practices.

PubMed Central

Brenner, S H; McKinin, E J

1989-01-01

A random sample of fifty nursing articles indexed in both MEDLINE and CINAHL (NURSING & ALLIED HEALTH) during 1986 was used for comparing indexing practices. Indexing was analyzed by counting the number of major descriptors, the number of major and minor descriptors, the number of indexing access points, the number of common indexing access points, and the number and type of unique indexing access points. The study results indicate: there are few differences in the number of major descriptors used, MEDLINE uses almost twice as many descriptors, MEDLINE has almost twice as many indexing access points, and MEDLINE and CINAHL provide few common access points. PMID:2676049

Spherical harmonics coefficients for ligand-based virtual screening of cyclooxygenase inhibitors.

PubMed

Wang, Quan; Birod, Kerstin; Angioni, Carlo; Grösch, Sabine; Geppert, Tim; Schneider, Petra; Rupp, Matthias; Schneider, Gisbert

2011-01-01

Molecular descriptors are essential for many applications in computational chemistry, such as ligand-based similarity searching. Spherical harmonics have previously been suggested as comprehensive descriptors of molecular structure and properties. We investigate a spherical harmonics descriptor for shape-based virtual screening. We introduce and validate a partially rotation-invariant three-dimensional molecular shape descriptor based on the norm of spherical harmonics expansion coefficients. Using this molecular representation, we parameterize molecular surfaces, i.e., isosurfaces of spatial molecular property distributions. We validate the shape descriptor in a comprehensive retrospective virtual screening experiment. In a prospective study, we virtually screen a large compound library for cyclooxygenase inhibitors, using a self-organizing map as a pre-filter and the shape descriptor for candidate prioritization. 12 compounds were tested in vitro for direct enzyme inhibition and in a whole blood assay. Active compounds containing a triazole scaffold were identified as direct cyclooxygenase-1 inhibitors. This outcome corroborates the usefulness of spherical harmonics for representation of molecular shape in virtual screening of large compound collections. The combination of pharmacophore and shape-based filtering of screening candidates proved to be a straightforward approach to finding novel bioactive chemotypes with minimal experimental effort.

A Concise Guide to Feature Histograms with Applications to LIDAR-Based Spacecraft Relative Navigation

NASA Astrophysics Data System (ADS)

Rhodes, Andrew P.; Christian, John A.; Evans, Thomas

2017-12-01

With the availability and popularity of 3D sensors, it is advantageous to re-examine the use of point cloud descriptors for the purpose of pose estimation and spacecraft relative navigation. One popular descriptor is the oriented unique repeatable clustered viewpoint feature histogram (OUR-CVFH), which is most often utilized in personal and industrial robotics to simultaneously recognize and navigate relative to an object. Recent research into using the OUR-CVFH descriptor for spacecraft navigation has produced favorable results. Since OUR-CVFH is the most recent innovation in a large family of feature histogram point cloud descriptors, discussions of parameter settings and insights into its functionality are spread among various publications and online resources. This paper organizes the history of feature histogram point cloud descriptors for a straightforward explanation of their evolution. This article compiles all the requisite information needed to implement OUR-CVFH into one location, as well as providing useful suggestions on how to tune the generation parameters. This work is beneficial for anyone interested in using this histogram descriptor for object recognition or navigation - may it be personal robotics or spacecraft navigation.

ANN expert system screening for illicit amphetamines using molecular descriptors

NASA Astrophysics Data System (ADS)

Gosav, S.; Praisler, M.; Dorohoi, D. O.

2007-05-01

The goal of this study was to develop and an artificial neural network (ANN) based on computed descriptors, which would be able to classify the molecular structures of potential illicit amphetamines and to derive their biological activity according to the similarity of their molecular structure with amphetamines of known toxicity. The system is necessary for testing new molecular structures for epidemiological, clinical, and forensic purposes. It was built using a database formed by 146 compounds representing drugs of abuse (mainly central stimulants, hallucinogens, sympathomimetic amines, narcotics and other potent analgesics), precursors, or derivatized counterparts. Their molecular structures were characterized by computing three types of descriptors: 38 constitutional descriptors (CDs), 69 topological descriptors (TDs) and 160 3D-MoRSE descriptors (3DDs). An ANN system was built for each category of variables. All three networks (CD-NN, TD-NN and 3DD-NN) were trained to distinguish between stimulant amphetamines, hallucinogenic amphetamines, and nonamphetamines. A selection of variables was performed when necessary. The efficiency with which each network identifies the class identity of an unknown sample was evaluated by calculating several figures of merit. The results of the comparative analysis are presented.

Can we apply the MRI BI-RADS lexicon morphology descriptors on contrast-enhanced spectral mammography?

PubMed

Kamal, Rasha M; Helal, Maha H; Mansour, Sahar M; Haggag, Marwa A; Nada, Omniya M; Farahat, Iman G; Alieldin, Nelly H

2016-07-12

To assess the feasibility of using the MRI breast imaging reporting and data system (BI-RADS) lexicon morphology descriptors to characterize enhancing breast lesions identified on contrast-enhanced spectral mammography (CESM). The study is a retrospective analysis of the morphology descriptors of 261 enhancing breast lesions identified on CESM in 239 patients. We presented the morphological categorization of the included lesions into focus, mass and non-mass. Further classifications included (1) the multiplicity for "focus" category, (2) the shape, margin and internal enhancement for "mass" category and (3) the distribution and internal enhancement for "non-mass" category. Each morphology descriptor was evaluated individually (irrespective of all other descriptors) by calculating its sensitivity, specificity, positive-predictive value (PPV) and negative-predictive value (NPV) and likelihood ratios (LRs). The study included 68/261 (26.1%) benign lesions and 193/261 (73.9%) malignant lesions. Intensely enhancing foci, whether single (7/12, 58.3%) or multiple (2/12, 16.7%), were malignant. Descriptors of "irregular"-shape (PPV: 92.4%) and "non-circumscribed" margin (odds ratio: 55.2, LR positive: 4.77; p-value: <0.001) were more compatible with malignancy. Internal mass enhancement patterns showed a very low specificity (58.0%) and NPV (40.0%). Non-mass enhancement (NME) was detected in 81/261 lesions. Asymmetrical NME in 81% (n = 52/81) lesions was malignant lesions and internal enhancement patterns indicative of malignancy were the heterogeneous and clumped ones. We can apply the MRI morphology descriptors to characterize lesions on CESM, but with few expectations. In many situations, irregular-shaped, non-circumscribed masses and NME with focal, ductal or segmental distribution and heterogeneous or clumped enhancement are the most suggestive descriptors of malignant pathologies. (1) The MRI BI-RADS lexicon morphology descriptors can be applied in the characterization of enhancing lesions on CESM with a few exceptions. (2) Multiple bilateral intensely enhancing foci should not be included under the normal background parenchymal enhancement unless they are proved to be benign by biopsy. (3) Mass lesion features that indicated malignancy were irregular-shaped, spiculated and irregular margins and heterogeneous internal enhancement patterns. The rim enhancement pattern should not be considered as a descriptor of malignant lesions unless CESM is coupled with an ultrasound examination.

Can we apply the MRI BI-RADS lexicon morphology descriptors on contrast-enhanced spectral mammography?

PubMed Central

Kamal, Rasha M; Helal, Maha H; Haggag, Marwa A; Nada, Omniya M; Farahat, Iman G; Alieldin, Nelly H

2016-01-01

Objective: To assess the feasibility of using the MRI breast imaging reporting and data system (BI-RADS) lexicon morphology descriptors to characterize enhancing breast lesions identified on contrast-enhanced spectral mammography (CESM). Methods: The study is a retrospective analysis of the morphology descriptors of 261 enhancing breast lesions identified on CESM in 239 patients. We presented the morphological categorization of the included lesions into focus, mass and non-mass. Further classifications included (1) the multiplicity for “focus” category, (2) the shape, margin and internal enhancement for “mass” category and (3) the distribution and internal enhancement for “non-mass” category. Each morphology descriptor was evaluated individually (irrespective of all other descriptors) by calculating its sensitivity, specificity, positive-predictive value (PPV) and negative-predictive value (NPV) and likelihood ratios (LRs). Results: The study included 68/261 (26.1%) benign lesions and 193/261 (73.9%) malignant lesions. Intensely enhancing foci, whether single (7/12, 58.3%) or multiple (2/12, 16.7%), were malignant. Descriptors of “irregular”-shape (PPV: 92.4%) and “non-circumscribed” margin (odds ratio: 55.2, LR positive: 4.77; p-value: <0.001) were more compatible with malignancy. Internal mass enhancement patterns showed a very low specificity (58.0%) and NPV (40.0%). Non-mass enhancement (NME) was detected in 81/261 lesions. Asymmetrical NME in 81% (n = 52/81) lesions was malignant lesions and internal enhancement patterns indicative of malignancy were the heterogeneous and clumped ones. Conclusion: We can apply the MRI morphology descriptors to characterize lesions on CESM, but with few expectations. In many situations, irregular-shaped, non-circumscribed masses and NME with focal, ductal or segmental distribution and heterogeneous or clumped enhancement are the most suggestive descriptors of malignant pathologies. Advances in knowledge: (1) The MRI BI-RADS lexicon morphology descriptors can be applied in the characterization of enhancing lesions on CESM with a few exceptions. (2) Multiple bilateral intensely enhancing foci should not be included under the normal background parenchymal enhancement unless they are proved to be benign by biopsy. (3) Mass lesion features that indicated malignancy were irregular-shaped, spiculated and irregular margins and heterogeneous internal enhancement patterns. The rim enhancement pattern should not be considered as a descriptor of malignant lesions unless CESM is coupled with an ultrasound examination. PMID:27327403

Heritabilities and genetic correlations in the same traits across different strata of herds created according to continuous genomic, genetic, and phenotypic descriptors.

PubMed

Yin, Tong; König, Sven

2018-03-01

The most common approach in dairy cattle to prove genotype by environment interactions is a multiple-trait model application, and considering the same traits in different environments as different traits. We enhanced such concepts by defining continuous phenotypic, genetic, and genomic herd descriptors, and applying random regression sire models. Traits of interest were test-day traits for milk yield, fat percentage, protein percentage, and somatic cell score, considering 267,393 records from 32,707 first-lactation Holstein cows. Cows were born in the years 2010 to 2013, and kept in 52 large-scale herds from 2 federal states of north-east Germany. The average number of genotyped cows per herd (45,613 single nucleotide polymorphism markers per cow) was 133.5 (range: 45 to 415 genotyped cows). Genomic herd descriptors were (1) the level of linkage disequilibrium (r 2 ) within specific chromosome segments, and (2) the average allele frequency for single nucleotide polymorphisms in close distance to a functional mutation. Genetic herd descriptors were the (1) intra-herd inbreeding coefficient, and (2) the percentage of daughters from foreign sires. Phenotypic herd descriptors were (1) herd size, and (2) the herd mean for nonreturn rate. Most correlations among herd descriptors were close to 0, indicating independence of genomic, genetic, and phenotypic characteristics. Heritabilities for milk yield increased with increasing intra-herd linkage disequilibrium, inbreeding, and herd size. Genetic correlations in same traits between adjacent levels of herd descriptors were close to 1, but declined for descriptor levels in greater distance. Genetic correlation declines were more obvious for somatic cell score, compared with test-day traits with larger heritabilities (fat percentage and protein percentage). Also, for milk yield, alterations of herd descriptor levels had an obvious effect on heritabilities and genetic correlations. By trend, multiple trait model results (based on created discrete herd classes) confirmed the random regression estimates. Identified alterations of breeding values in dependency of herd descriptors suggest utilization of specific sires for specific herd structures, offering new possibilities to improve sire selection strategies. Regarding genomic selection designs and genetic gain transfer into commercial herds, cow herds for the utilization in cow training sets should reflect the genomic, genetic, and phenotypic pattern of the broad population. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

A Competency-Based Framework for Graduate-Level Health Educators.

ERIC Educational Resources Information Center

American Alliance for Health, Physical Education, Recreation and Dance, Reston, VA. American Association for Health Education.

This document builds on the 1997 Standards for the Preparation of Graduate-Level Health Educators by including expanded content descriptors and objectives for the graduate level competencies. It begins by discussing evolution of health education competencies; chronology of the graduate standard development process; benefits of graduate level…

Classifying Measures of Biological Variation

PubMed Central

Gregorius, Hans-Rolf; Gillet, Elizabeth M.

2015-01-01

Biological variation is commonly measured at two basic levels: variation within individual communities, and the distribution of variation over communities or within a metacommunity. We develop a classification for the measurement of biological variation on both levels: Within communities into the categories of dispersion and diversity, and within metacommunities into the categories of compositional differentiation and partitioning of variation. There are essentially two approaches to characterizing the distribution of trait variation over communities in that individuals with the same trait state or type tend to occur in the same community (describes differentiation tendencies), and individuals with different types tend to occur in different communities (describes apportionment tendencies). Both approaches can be viewed from the dual perspectives of trait variation distributed over communities (CT perspective) and community membership distributed over trait states (TC perspective). This classification covers most of the relevant descriptors (qualified measures) of biological variation, as is demonstrated with the help of major families of descriptors. Moreover, the classification is shown to open ways to develop new descriptors that meet current needs. Yet the classification also reveals the misclassification of some prominent and widely applied descriptors: Dispersion is often misclassified as diversity, particularly in cases where dispersion descriptor allow for the computation of effective numbers; the descriptor GST of population genetics is commonly misclassified as compositional differentiation and confused with partitioning-oriented differentiation, whereas it actually measures partitioning-oriented apportionment; descriptors of β-diversity are ambiguous about the differentiation effects they are supposed to represent and therefore require conceptual reconsideration. PMID:25807558

Application of ant colony optimization in development of models for prediction of anti-HIV-1 activity of HEPT derivatives.

PubMed

Zare-Shahabadi, Vali; Abbasitabar, Fatemeh

2010-09-01

Quantitative structure-activity relationship models were derived for 107 analogs of 1-[(2-hydroxyethoxy) methyl]-6-(phenylthio)thymine, a potent inhibitor of the HIV-1 reverse transcriptase. The activities of these compounds were investigated by means of multiple linear regression (MLR) technique. An ant colony optimization algorithm, called Memorized_ACS, was applied for selecting relevant descriptors and detecting outliers. This algorithm uses an external memory based upon knowledge incorporation from previous iterations. At first, the memory is empty, and then it is filled by running several ACS algorithms. In this respect, after each ACS run, the elite ant is stored in the memory and the process is continued to fill the memory. Here, pheromone updating is performed by all elite ants collected in the memory; this results in improvements in both exploration and exploitation behaviors of the ACS algorithm. The memory is then made empty and is filled again by performing several ACS algorithms using updated pheromone trails. This process is repeated for several iterations. At the end, the memory contains several top solutions for the problem. Number of appearance of each descriptor in the external memory is a good criterion for its importance. Finally, prediction is performed by the elitist ant, and interpretation is carried out by considering the importance of each descriptor. The best MLR model has a training error of 0.47 log (1/EC(50)) units (R(2) = 0.90) and a prediction error of 0.76 log (1/EC(50)) units (R(2) = 0.88). Copyright 2010 Wiley Periodicals, Inc.

Target recognition for ladar range image using slice image

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Wang, Liang

2015-12-01

A shape descriptor and a complete shape-based recognition system using slice images as geometric feature descriptor for ladar range images are introduced. A slice image is a two-dimensional image generated by three-dimensional Hough transform and the corresponding mathematical transformation. The system consists of two processes, the model library construction and recognition. In the model library construction process, a series of range images are obtained after the model object is sampled at preset attitude angles. Then, all the range images are converted into slice images. The number of slice images is reduced by clustering analysis and finding a representation to reduce the size of the model library. In the recognition process, the slice image of the scene is compared with the slice image in the model library. The recognition results depend on the comparison. Simulated ladar range images are used to analyze the recognition and misjudgment rates, and comparison between the slice image representation method and moment invariants representation method is performed. The experimental results show that whether in conditions without noise or with ladar noise, the system has a high recognition rate and low misjudgment rate. The comparison experiment demonstrates that the slice image has better representation ability than moment invariants.

Levels-of-processing effects on a task of olfactory naming.

PubMed

Royet, Jean-Pierre; Koenig, Olivier; Paugam-Moisy, Helene; Puzenat, Didier; Chasse, Jean-Luc

2004-02-01

The effects of odor processing were investigated at various analytical levels, from simple sensory analysis to deep or semantic analysis, on a subsequent task of odor naming. Students (106 women, 23.6 +/- 5.5 yr. old; 65 men, 25.1 +/- 7.1 yr. old) were tested. The experimental procedure included two successive sessions, a first session to characterize a set of 30 odors with criteria that used various depths of processing and a second session to name the odors as quickly as possible. Four processing conditions rated the odors using descriptors before naming the odor. The control condition did not rate the odors before naming. The processing conditions were based on lower-level olfactory judgments (superficial processing), higher-level olfactory-gustatory-somesthetic judgments (deep processing), and higher-level nonolfactory judgments (Deep-Control processing, with subjects rating odors with auditory and visual descriptors). One experimental condition successively grouped lower- and higher-level olfactory judgments (Superficial-Deep processing). A naming index which depended on response accuracy and the subjects' response time were calculated. Odor naming was modified for 18 out of 30 odorants as a function of the level of processing required. For 94.5% of significant variations, the scores for odor naming were higher following those tasks for which it was hypothesized that the necessary olfactory processing was carried out at a deeper level. Performance in the naming task was progressively improved as follows: no rating of odors, then superficial, deep-control, deep, and superficial-deep processings. These data show that the deepest olfactory encoding was later associated with progressively higher performance in naming.

Computer-Aided Diagnosis of Solid Breast Lesions Using an Ultrasonic Multi-Feature Analysis Procedure

DTIC Science & Technology

2011-01-01

areas. We quantified morphometric features by geometric and fractal analysis of traced lesion boundaries. Although no single parameter can reliably...These include acoustic descriptors (“echogenicity,” “heterogeneity,” “shadowing”) and morphometric descriptors (“area,” “aspect ratio,” “border...quantitative descriptors; some morphometric features (such as border irregularity) also were particularly effective in lesion classification. Our

QSAR modeling of human serum protein binding with several modeling techniques utilizing structure-information representation.

PubMed

Votano, Joseph R; Parham, Marc; Hall, L Mark; Hall, Lowell H; Kier, Lemont B; Oloff, Scott; Tropsha, Alexander

2006-11-30

Four modeling techniques, using topological descriptors to represent molecular structure, were employed to produce models of human serum protein binding (% bound) on a data set of 1008 experimental values, carefully screened from publicly available sources. To our knowledge, this data is the largest set on human serum protein binding reported for QSAR modeling. The data was partitioned into a training set of 808 compounds and an external validation test set of 200 compounds. Partitioning was accomplished by clustering the compounds in a structure descriptor space so that random sampling of 20% of the whole data set produced an external test set that is a good representative of the training set with respect to both structure and protein binding values. The four modeling techniques include multiple linear regression (MLR), artificial neural networks (ANN), k-nearest neighbors (kNN), and support vector machines (SVM). With the exception of the MLR model, the ANN, kNN, and SVM QSARs were ensemble models. Training set correlation coefficients and mean absolute error ranged from r2=0.90 and MAE=7.6 for ANN to r2=0.61 and MAE=16.2 for MLR. Prediction results from the validation set yielded correlation coefficients and mean absolute errors which ranged from r2=0.70 and MAE=14.1 for ANN to a low of r2=0.59 and MAE=18.3 for the SVM model. Structure descriptors that contribute significantly to the models are discussed and compared with those found in other published models. For the ANN model, structure descriptor trends with respect to their affects on predicted protein binding can assist the chemist in structure modification during the drug design process.

A Framework of Temporal-Spatial Descriptors-Based Feature Extraction for Improved Myoelectric Pattern Recognition.

PubMed

Khushaba, Rami N; Al-Timemy, Ali H; Al-Ani, Ahmed; Al-Jumaily, Adel

2017-10-01

The extraction of the accurate and efficient descriptors of muscular activity plays an important role in tackling the challenging problem of myoelectric control of powered prostheses. In this paper, we present a new feature extraction framework that aims to give an enhanced representation of muscular activities through increasing the amount of information that can be extracted from individual and combined electromyogram (EMG) channels. We propose to use time-domain descriptors (TDDs) in estimating the EMG signal power spectrum characteristics; a step that preserves the computational power required for the construction of spectral features. Subsequently, TDD is used in a process that involves: 1) representing the temporal evolution of the EMG signals by progressively tracking the correlation between the TDD extracted from each analysis time window and a nonlinearly mapped version of it across the same EMG channel and 2) representing the spatial coherence between the different EMG channels, which is achieved by calculating the correlation between the TDD extracted from the differences of all possible combinations of pairs of channels and their nonlinearly mapped versions. The proposed temporal-spatial descriptors (TSDs) are validated on multiple sparse and high-density (HD) EMG data sets collected from a number of intact-limbed and amputees performing a large number of hand and finger movements. Classification results showed significant reductions in the achieved error rates in comparison to other methods, with the improvement of at least 8% on average across all subjects. Additionally, the proposed TSDs achieved significantly well in problems with HD-EMG with average classification errors of <5% across all subjects using windows lengths of 50 ms only.

Staging Lung Cancer: Metastasis.

PubMed

Shroff, Girish S; Viswanathan, Chitra; Carter, Brett W; Benveniste, Marcelo F; Truong, Mylene T; Sabloff, Bradley S

2018-05-01

The updated eighth edition of the tumor, node, metastasis (TNM) classification for lung cancer includes revisions to T and M descriptors. In terms of the M descriptor, the classification of intrathoracic metastatic disease as M1a is unchanged from TNM-7. Extrathoracic metastatic disease, which was classified as M1b in TNM-7, is now subdivided into M1b (single metastasis, single organ) and M1c (multiple metastases in one or multiple organs) descriptors. In this article, the rationale for changes in the M descriptors, the utility of preoperative staging with PET/computed tomography, and the treatment options available for patients with oligometastatic disease are discussed. Copyright © 2018 Elsevier Inc. All rights reserved.

A Multistage Approach for Image Registration.

PubMed

Bowen, Francis; Hu, Jianghai; Du, Eliza Yingzi

2016-09-01

Successful image registration is an important step for object recognition, target detection, remote sensing, multimodal content fusion, scene blending, and disaster assessment and management. The geometric and photometric variations between images adversely affect the ability for an algorithm to estimate the transformation parameters that relate the two images. Local deformations, lighting conditions, object obstructions, and perspective differences all contribute to the challenges faced by traditional registration techniques. In this paper, a novel multistage registration approach is proposed that is resilient to view point differences, image content variations, and lighting conditions. Robust registration is realized through the utilization of a novel region descriptor which couples with the spatial and texture characteristics of invariant feature points. The proposed region descriptor is exploited in a multistage approach. A multistage process allows the utilization of the graph-based descriptor in many scenarios thus allowing the algorithm to be applied to a broader set of images. Each successive stage of the registration technique is evaluated through an effective similarity metric which determines subsequent action. The registration of aerial and street view images from pre- and post-disaster provide strong evidence that the proposed method estimates more accurate global transformation parameters than traditional feature-based methods. Experimental results show the robustness and accuracy of the proposed multistage image registration methodology.

Accurate prediction of RNA-binding protein residues with two discriminative structural descriptors.

PubMed

Sun, Meijian; Wang, Xia; Zou, Chuanxin; He, Zenghui; Liu, Wei; Li, Honglin

2016-06-07

RNA-binding proteins participate in many important biological processes concerning RNA-mediated gene regulation, and several computational methods have been recently developed to predict the protein-RNA interactions of RNA-binding proteins. Newly developed discriminative descriptors will help to improve the prediction accuracy of these prediction methods and provide further meaningful information for researchers. In this work, we designed two structural features (residue electrostatic surface potential and triplet interface propensity) and according to the statistical and structural analysis of protein-RNA complexes, the two features were powerful for identifying RNA-binding protein residues. Using these two features and other excellent structure- and sequence-based features, a random forest classifier was constructed to predict RNA-binding residues. The area under the receiver operating characteristic curve (AUC) of five-fold cross-validation for our method on training set RBP195 was 0.900, and when applied to the test set RBP68, the prediction accuracy (ACC) was 0.868, and the F-score was 0.631. The good prediction performance of our method revealed that the two newly designed descriptors could be discriminative for inferring protein residues interacting with RNAs. To facilitate the use of our method, a web-server called RNAProSite, which implements the proposed method, was constructed and is freely available at http://lilab.ecust.edu.cn/NABind .

'Just gripping my heart and squeezing': Naming and explaining the emotional experience of receiving bad news in the paediatric oncology setting.

PubMed

Nelson, Mia; Kelly, Daniel; McAndrew, Rachel; Smith, Pam

2017-09-01

To explore recipients' perspectives on the range and origins of their emotional experiences during their 'bad news' consultations. Participants were four bereaved families of children who had changed from active treatment to palliative care in paediatric oncology. Data was collected using emotional touchpoint storytelling. The names (descriptors) given to the emotional experiences were linguistically classified. Explanations of their perceived origins were examined using applied thematic analysis. 26 descriptors were given, relating to bodily sensations, affective states, evaluations and cognitive conditions. Three themes were identified in the origins of these experiences - 'becoming aware', 'the changes' and 'being in this situation'. Parents described strong emotional displays during the consultation including physical collapse. These related to the internal process of 'becoming aware'. Three descriptors were given as originating from the clinicians and their delivery of the news - 'supported', 'included', 'trusting'. Recipients perceive their emotional experiences as mainly originating from the news itself, and perceived consequences of it, rather than its delivery. Strong emotional reactions during the interaction are not necessarily an indicator of ineffectual delivery. Findings offer a thematic framing that may support and deepen practitioners understanding of recipients' emotional reactions during bad news consultations. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Predictive Modeling of Chemical Hazard by Integrating Numerical Descriptors of Chemical Structures and Short-term Toxicity Assay Data

PubMed Central

Rusyn, Ivan; Sedykh, Alexander; Guyton, Kathryn Z.; Tropsha, Alexander

2012-01-01

Quantitative structure-activity relationship (QSAR) models are widely used for in silico prediction of in vivo toxicity of drug candidates or environmental chemicals, adding value to candidate selection in drug development or in a search for less hazardous and more sustainable alternatives for chemicals in commerce. The development of traditional QSAR models is enabled by numerical descriptors representing the inherent chemical properties that can be easily defined for any number of molecules; however, traditional QSAR models often have limited predictive power due to the lack of data and complexity of in vivo endpoints. Although it has been indeed difficult to obtain experimentally derived toxicity data on a large number of chemicals in the past, the results of quantitative in vitro screening of thousands of environmental chemicals in hundreds of experimental systems are now available and continue to accumulate. In addition, publicly accessible toxicogenomics data collected on hundreds of chemicals provide another dimension of molecular information that is potentially useful for predictive toxicity modeling. These new characteristics of molecular bioactivity arising from short-term biological assays, i.e., in vitro screening and/or in vivo toxicogenomics data can now be exploited in combination with chemical structural information to generate hybrid QSAR–like quantitative models to predict human toxicity and carcinogenicity. Using several case studies, we illustrate the benefits of a hybrid modeling approach, namely improvements in the accuracy of models, enhanced interpretation of the most predictive features, and expanded applicability domain for wider chemical space coverage. PMID:22387746

A general structure-property relationship to predict the enthalpy of vaporisation at ambient temperatures.

PubMed

Oberg, T

2007-01-01

The vapour pressure is the most important property of an anthropogenic organic compound in determining its partitioning between the atmosphere and the other environmental media. The enthalpy of vaporisation quantifies the temperature dependence of the vapour pressure and its value around 298 K is needed for environmental modelling. The enthalpy of vaporisation can be determined by different experimental methods, but estimation methods are needed to extend the current database and several approaches are available from the literature. However, these methods have limitations, such as a need for other experimental results as input data, a limited applicability domain, a lack of domain definition, and a lack of predictive validation. Here we have attempted to develop a quantitative structure-property relationship (QSPR) that has general applicability and is thoroughly validated. Enthalpies of vaporisation at 298 K were collected from the literature for 1835 pure compounds. The three-dimensional (3D) structures were optimised and each compound was described by a set of computationally derived descriptors. The compounds were randomly assigned into a calibration set and a prediction set. Partial least squares regression (PLSR) was used to estimate a low-dimensional QSPR model with 12 latent variables. The predictive performance of this model, within the domain of application, was estimated at n=560, q2Ext=0.968 and s=0.028 (log transformed values). The QSPR model was subsequently applied to a database of 100,000+ structures, after a similar 3D optimisation and descriptor generation. Reliable predictions can be reported for compounds within the previously defined applicability domain.

Learning physical descriptors for materials science by compressed sensing

NASA Astrophysics Data System (ADS)

Ghiringhelli, Luca M.; Vybiral, Jan; Ahmetcik, Emre; Ouyang, Runhai; Levchenko, Sergey V.; Draxl, Claudia; Scheffler, Matthias

2017-02-01

The availability of big data in materials science offers new routes for analyzing materials properties and functions and achieving scientific understanding. Finding structure in these data that is not directly visible by standard tools and exploitation of the scientific information requires new and dedicated methodology based on approaches from statistical learning, compressed sensing, and other recent methods from applied mathematics, computer science, statistics, signal processing, and information science. In this paper, we explain and demonstrate a compressed-sensing based methodology for feature selection, specifically for discovering physical descriptors, i.e., physical parameters that describe the material and its properties of interest, and associated equations that explicitly and quantitatively describe those relevant properties. As showcase application and proof of concept, we describe how to build a physical model for the quantitative prediction of the crystal structure of binary compound semiconductors.

Using Theoretical Descriptions in Structure Activity Relations. 3. Electronic Descriptors

DTIC Science & Technology

1988-08-01

Activity Relationships (QSAR) have been used successfully in the past to develop predictive equations for several biological and physical properties...Linear Free Energy Relationships (,FF.3) and is based on work by Hammet in which he derived electronic descriptors for the dissociation of substituted...structure of a compound and its activity in a system. Several different structural descriptors have been used in QSAR equations . These range from

Building Scientific Confidence in the Development and ...

EPA Pesticide Factsheets

Read-across remains a popular data gap filling technique within category and analogue approaches for regulatory purposes. Acceptance of read-across is an ongoing challenge with several efforts underway for identifying and addressing uncertainties. Here we demonstrate an algorithmic approach to facilitate read-across using ToxCast in vitro bioactivity data in conjunction with chemical descriptor information to predict in vivo outcomes in guideline testing studies from ToxRefDB. Over 3400 different chemical structure descriptors were generated for a set of 976 chemicals and supplemented with the outcomes from 821 in vitro assays. The read-across prediction for a given chemical was based on the similarity weighted endpoint outcomes of its nearest neighbors calculated using in vitro bioactivity and chemical structure descriptors, called GenRA. GenRA is based on a computational approach for: (i) defining local validity domains using chemical and bioactivity descriptors, (ii) systematically deriving endpoint read-across predictions within these domains using similarity weighted activity of nearest neighbours, (iii) objectively evaluating predicted performance using tested chemicals, and (iv) assigning read-across predictions to untested chemicals along with estimates of uncertainty. We found in vitro bioactivity descriptors were often found to be more predictive of in vivo toxicity outcomes than chemical structure descriptors. We believe GenRA is an important first st

Developing descriptors to predict mechanical properties of nanotubes.

PubMed

Borders, Tammie L; Fonseca, Alexandre F; Zhang, Hengji; Cho, Kyeongjae; Rusinko, Andrew

2013-04-22

Descriptors and quantitative structure property relationships (QSPR) were investigated for mechanical property prediction of carbon nanotubes (CNTs). 78 molecular dynamics (MD) simulations were carried out, and 20 descriptors were calculated to build quantitative structure property relationships (QSPRs) for Young's modulus and Poisson's ratio in two separate analyses: vacancy only and vacancy plus methyl functionalization. In the first analysis, C(N2)/C(T) (number of non-sp2 hybridized carbons per the total carbons) and chiral angle were identified as critical descriptors for both Young's modulus and Poisson's ratio. Further analysis and literature findings indicate the effect of chiral angle is negligible at larger CNT radii for both properties. Raman spectroscopy can be used to measure C(N2)/C(T), providing a direct link between experimental and computational results. Poisson's ratio approaches two different limiting values as CNT radii increases: 0.23-0.25 for chiral and armchair CNTs and 0.10 for zigzag CNTs (surface defects <3%). In the second analysis, the critical descriptors were C(N2)/C(T), chiral angle, and M(N)/C(T) (number of methyl groups per total carbons). These results imply new types of defects can be represented as a new descriptor in QSPR models. Finally, results are qualified and quantified against experimental data.

Human response to vibration in residential environments.

PubMed

Waddington, David C; Woodcock, James; Peris, Eulalia; Condie, Jenna; Sica, Gennaro; Moorhouse, Andrew T; Steele, Andy

2014-01-01

This paper presents the main findings of a field survey conducted in the United Kingdom into the human response to vibration in residential environments. The main aim of this study was to derive exposure-response relationships for annoyance due to vibration from environmental sources. The sources of vibration considered in this paper are railway and construction activity. Annoyance data were collected using questionnaires conducted face-to-face with residents in their own homes. Questionnaires were completed with residents exposed to railway induced vibration (N = 931) and vibration from the construction of a light rail system (N = 350). Measurements of vibration were conducted at internal and external positions from which estimates of 24-h vibration exposure were derived for 1073 of the case studies. Sixty different vibration exposure descriptors along with 6 different frequency weightings were assessed as potential predictors of annoyance. Of the exposure descriptors considered, none were found to be a better predictor of annoyance than any other. However, use of relevant frequency weightings was found to improve correlation between vibration exposure and annoyance. A unified exposure-response relationship could not be derived due to differences in response to the two sources so separate relationships are presented for each source.

Contour matching for a fish recognition and migration-monitoring system

NASA Astrophysics Data System (ADS)

Lee, Dah-Jye; Schoenberger, Robert B.; Shiozawa, Dennis; Xu, Xiaoqian; Zhan, Pengcheng

2004-12-01

Fish migration is being monitored year round to provide valuable information for the study of behavioral responses of fish to environmental variations. However, currently all monitoring is done by human observers. An automatic fish recognition and migration monitoring system is more efficient and can provide more accurate data. Such a system includes automatic fish image acquisition, contour extraction, fish categorization, and data storage. Shape is a very important characteristic and shape analysis and shape matching are studied for fish recognition. Previous work focused on finding critical landmark points on fish shape using curvature function analysis. Fish recognition based on landmark points has shown satisfying results. However, the main difficulty of this approach is that landmark points sometimes cannot be located very accurately. Whole shape matching is used for fish recognition in this paper. Several shape descriptors, such as Fourier descriptors, polygon approximation and line segments, are tested. A power cepstrum technique has been developed in order to improve the categorization speed using contours represented in tangent space with normalized length. Design and integration including image acquisition, contour extraction and fish categorization are discussed in this paper. Fish categorization results based on shape analysis and shape matching are also included.

Pain Quality Descriptors in Community-Dwelling Older Adults with Nonmalignant Pain

PubMed Central

Thakral, Manu; Shi, Ling; Foust, Janice B.; Patel, Kushang V.; Shmerling, Robert H.; Bean, Jonathan F.; Leveille, Suzanne G.

2016-01-01

This study aimed to characterize the prevalence of various pain qualities in older adults with chronic non-malignant pain and determine the association of pain quality to other pain characteristics namely: severity, interference distribution, and pain-associated conditions. In the population-based MOBILIZE Boston Study, 560 participants aged≥70 years reported chronic pain in the baseline assessment, which included a home interview and clinic exam. Pain quality was assessed using a modified version of the McGill Pain Questionnaire (MPQ) consisting of 20 descriptors, from which 3 categories were derived: cognitive/affective, sensory and neuropathic. Presence of ≥2 pain-associated conditions was significantly associated with 18 of the 20 pain quality descriptors. Sensory descriptors were endorsed by nearly all older adults with chronic pain (93%), followed by cognitive/affective (83.4%) and neuropathic descriptors (68.6%). Neuropathic descriptors were associated with the greatest number of pain-associated conditions including osteoarthritis of the hand and knee. More than half of participants (59%) endorsed descriptors in all 3 categories and had more severe pain and interference, and multi-site or widespread pain than those endorsing 1 or 2 categories. Strong associations were observed between pain quality and measures of pain severity, interference, and distribution (p<.0001). Findings from this study indicate that older adults have multiple pain-associated conditions which likely reflect multiple physiological mechanisms for pain. Linking pain qualities with other associated pain characteristics serves to develop a multidimensional approach to geriatric pain assessment. Future research is needed to investigate the physiological mechanisms responsible for the variability in pain qualities endorsed by older adults. PMID:27842050

Establishment of an in silico phototoxicity prediction method by combining descriptors related to photo-absorption and photo-reaction.

PubMed

Haranosono, Yu; Kurata, Masaaki; Sakaki, Hideyuki

2014-08-01

One of the mechanisms of phototoxicity is photo-reaction, such as reactive oxygen species (ROS) generation following photo-absorption. We focused on ROS generation and photo-absorption as key-steps, because these key-steps are able to be described by photochemical properties, and these properties are dependent on chemical structure. Photo-reactivity of a compound is described by HOMO-LUMO Gap (HLG), generally. Herein, we showed that HLG can be used as a descriptor of the generation of reactive oxygen species. Moreover, the maximum-conjugated π electron number (PENMC), which we found as a descriptor of photo-absorption, could also predict in vitro phototoxicity. Each descriptor could predict in vitro phototoxicity with 70.0% concordance, but there was un-predicted area found (gray zone). Interestingly, some compounds in each gray zone were not common, indicating that the combination of two descriptors could improve prediction potential. We reset the cut-off lines to define positive zone, negative zone and gray zone for each descriptor. Thereby we overlapped HLG and PENMC in a graph, and divided the total area to nine zones with cut-off lines of each descriptor. The rules to prediction were decided to achieve the best concordance, and the concordances were improved up to 82.8% for self-validation, 81.6% for cross-validation. We found common properties among false positive or negative compounds, photo-reactive structure and photo-allergenic, respectively. In addition, our method could be adapted to compounds rich in structural diversity using only chemical structure without any statistical analysis and complicated calculation.

Pain quality descriptors in community-dwelling older adults with nonmalignant pain.

PubMed

Thakral, Manu; Shi, Ling; Foust, Janice B; Patel, Kushang V; Shmerling, Robert H; Bean, Jonathan F; Leveille, Suzanne G

2016-12-01

This study aimed to characterize the prevalence of various pain qualities in older adults with chronic nonmalignant pain and determine the association of pain quality to other pain characteristics namely: severity, interference, distribution, and pain-associated conditions. In the population-based MOBILIZE Boston Study, 560 participants aged ≥70 years reported chronic pain in the baseline assessment, which included a home interview and clinic exam. Pain quality was assessed using a modified version of the McGill Pain Questionnaire (MPQ) consisting of 20 descriptors from which 3 categories were derived: cognitive/affective, sensory, and neuropathic. Presence of ≥2 pain-associated conditions was significantly associated with 18 of the 20 pain quality descriptors. Sensory descriptors were endorsed by nearly all older adults with chronic pain (93%), followed by cognitive/affective (83.4%) and neuropathic descriptors (68.6%). Neuropathic descriptors were associated with the greatest number of pain-associated conditions including osteoarthritis of the hand and knee. More than half of participants (59%) endorsed descriptors in all 3 categories and had more severe pain and interference, and multisite or widespread pain than those endorsing 1 or 2 categories. Strong associations were observed between pain quality and measures of pain severity, interference, and distribution (P < 0.0001). Findings from this study indicate that older adults have multiple pain-associated conditions that likely reflect multiple physiological mechanisms for pain. Linking pain qualities with other associated pain characteristics serve to develop a multidimensional approach to geriatric pain assessment. Future research is needed to investigate the physiological mechanisms responsible for the variability in pain qualities endorsed by older adults.

Improving Large-Scale Image Retrieval Through Robust Aggregation of Local Descriptors.

PubMed

Husain, Syed Sameed; Bober, Miroslaw

2017-09-01

Visual search and image retrieval underpin numerous applications, however the task is still challenging predominantly due to the variability of object appearance and ever increasing size of the databases, often exceeding billions of images. Prior art methods rely on aggregation of local scale-invariant descriptors, such as SIFT, via mechanisms including Bag of Visual Words (BoW), Vector of Locally Aggregated Descriptors (VLAD) and Fisher Vectors (FV). However, their performance is still short of what is required. This paper presents a novel method for deriving a compact and distinctive representation of image content called Robust Visual Descriptor with Whitening (RVD-W). It significantly advances the state of the art and delivers world-class performance. In our approach local descriptors are rank-assigned to multiple clusters. Residual vectors are then computed in each cluster, normalized using a direction-preserving normalization function and aggregated based on the neighborhood rank. Importantly, the residual vectors are de-correlated and whitened in each cluster before aggregation, leading to a balanced energy distribution in each dimension and significantly improved performance. We also propose a new post-PCA normalization approach which improves separability between the matching and non-matching global descriptors. This new normalization benefits not only our RVD-W descriptor but also improves existing approaches based on FV and VLAD aggregation. Furthermore, we show that the aggregation framework developed using hand-crafted SIFT features also performs exceptionally well with Convolutional Neural Network (CNN) based features. The RVD-W pipeline outperforms state-of-the-art global descriptors on both the Holidays and Oxford datasets. On the large scale datasets, Holidays1M and Oxford1M, SIFT-based RVD-W representation obtains a mAP of 45.1 and 35.1 percent, while CNN-based RVD-W achieve a mAP of 63.5 and 44.8 percent, all yielding superior performance to the state-of-the-art.

Predicting Drug-induced Hepatotoxicity Using QSAR and Toxicogenomics Approaches

PubMed Central

Low, Yen; Uehara, Takeki; Minowa, Yohsuke; Yamada, Hiroshi; Ohno, Yasuo; Urushidani, Tetsuro; Sedykh, Alexander; Muratov, Eugene; Fourches, Denis; Zhu, Hao; Rusyn, Ivan; Tropsha, Alexander

2014-01-01

Quantitative Structure-Activity Relationship (QSAR) modeling and toxicogenomics are used independently as predictive tools in toxicology. In this study, we evaluated the power of several statistical models for predicting drug hepatotoxicity in rats using different descriptors of drug molecules, namely their chemical descriptors and toxicogenomic profiles. The records were taken from the Toxicogenomics Project rat liver microarray database containing information on 127 drugs (http://toxico.nibio.go.jp/datalist.html). The model endpoint was hepatotoxicity in the rat following 28 days of exposure, established by liver histopathology and serum chemistry. First, we developed multiple conventional QSAR classification models using a comprehensive set of chemical descriptors and several classification methods (k nearest neighbor, support vector machines, random forests, and distance weighted discrimination). With chemical descriptors alone, external predictivity (Correct Classification Rate, CCR) from 5-fold external cross-validation was 61%. Next, the same classification methods were employed to build models using only toxicogenomic data (24h after a single exposure) treated as biological descriptors. The optimized models used only 85 selected toxicogenomic descriptors and had CCR as high as 76%. Finally, hybrid models combining both chemical descriptors and transcripts were developed; their CCRs were between 68 and 77%. Although the accuracy of hybrid models did not exceed that of the models based on toxicogenomic data alone, the use of both chemical and biological descriptors enriched the interpretation of the models. In addition to finding 85 transcripts that were predictive and highly relevant to the mechanisms of drug-induced liver injury, chemical structural alerts for hepatotoxicity were also identified. These results suggest that concurrent exploration of the chemical features and acute treatment-induced changes in transcript levels will both enrich the mechanistic understanding of sub-chronic liver injury and afford models capable of accurate prediction of hepatotoxicity from chemical structure and short-term assay results. PMID:21699217

Relationship between Dyspnea Descriptors and Underlying Causes of the Symptom; a Cross-sectional Study

PubMed Central

Sajadi, Seyyed Mohammad Ali; Majidi, Alireza; Abdollahimajd, Fahimeh; jalali, Fatemeh

2017-01-01

Introduction: History taking and physical examination help clinicians identify the patient’s problem and effectively treat it. This study aimed to evaluate the descriptors of dyspnea in patients presenting to emergency department (ED) with asthma, congestive heart failure (CHF), and chronic obstructive pulmonary disease (COPD). Method: This cross-sectional study was conducted on all patients presenting to ED with chief complaint of dyspnea, during 2 years. The patients were asked to describe their dyspnea by choosing three items from the valid and reliable questionnaire or articulating their sensation. The relationship between dyspnea descriptors and underlying cause of symptom was evaluated using SPSS version 16. Results: 312 patients with the mean age of 60.96±17.01 years were evaluated (53.2% male). Most of the patients were > 65 years old (48.7%) and had basic level of education (76.9%). "My breath doesn’t go out all the way" with 83.1%, “My chest feels tight " with 45.8%, and "I feel that my airway is obstructed" with 40.7%, were the most frequent dyspnea descriptors in asthma patients. "My breathing requires work" with 46.3%, "I feel that I am suffocating" with 31.5%, and "My breath doesn’t go out all the way" with 29.6%, were the most frequent dyspnea descriptors in COPD patients. "My breathing is heavy" with 74.4%, "A hunger for more air” with 24.4%, and "I cannot get enough air" with 23.2%, were the most frequent dyspnea descriptors in CHF patients. Except for “My breath does not go in all the way”, there was significant correlation between studied dyspnea descriptors and underlying disease (p = 0.001 for all analyses). Conclusion: It seems that dyspnea descriptors along with other findings from history and physical examination could be helpful in differentiating the causes of the symptom in patients presenting to ED suffering from dyspnea. PMID:28894777

Relationship between Dyspnea Descriptors and Underlying Causes of the Symptom; a Cross-sectional Study.

PubMed

Sajadi, Seyyed Mohammad Ali; Majidi, Alireza; Abdollahimajd, Fahimeh; Jalali, Fatemeh

2017-01-01

History taking and physical examination help clinicians identify the patient's problem and effectively treat it. This study aimed to evaluate the descriptors of dyspnea in patients presenting to emergency department (ED) with asthma, congestive heart failure (CHF), and chronic obstructive pulmonary disease (COPD). This cross-sectional study was conducted on all patients presenting to ED with chief complaint of dyspnea, during 2 years. The patients were asked to describe their dyspnea by choosing three items from the valid and reliable questionnaire or articulating their sensation. The relationship between dyspnea descriptors and underlying cause of symptom was evaluated using SPSS version 16. 312 patients with the mean age of 60.96±17.01 years were evaluated (53.2% male). Most of the patients were > 65 years old (48.7%) and had basic level of education (76.9%). "My breath doesn't go out all the way" with 83.1%, "My chest feels tight " with 45.8%, and "I feel that my airway is obstructed" with 40.7%, were the most frequent dyspnea descriptors in asthma patients. "My breathing requires work" with 46.3%, "I feel that I am suffocating" with 31.5%, and "My breath doesn't go out all the way" with 29.6%, were the most frequent dyspnea descriptors in COPD patients. "My breathing is heavy" with 74.4%, "A hunger for more air" with 24.4%, and "I cannot get enough air" with 23.2%, were the most frequent dyspnea descriptors in CHF patients. Except for "My breath does not go in all the way", there was significant correlation between studied dyspnea descriptors and underlying disease (p = 0.001 for all analyses). It seems that dyspnea descriptors along with other findings from history and physical examination could be helpful in differentiating the causes of the symptom in patients presenting to ED suffering from dyspnea.

Microscopic structural descriptor of liquid water

NASA Astrophysics Data System (ADS)

Shi, Rui; Tanaka, Hajime

2018-03-01

The microscopic structure of liquid water has been believed to be the key to the understanding of the unique properties of this extremely important substance. Many structural descriptors have been developed for revealing local structural order in water, but their properties are still not well understood. The essential difficulty comes from structural fluctuations due to thermal noise, which are intrinsic to the liquid state. The most popular and widely used descriptors are the local structure index (LSI) and d5. Recently, Russo and Tanaka [Nat. Commun. 3, 3556 (2014)] introduced a new descriptor ζ which measures the translational order between the first and second shells considering hydrogen bonding (H-bonding) in the first shell. In this work, we compare the performance of these three structural descriptors for a popular water model known as TIP5P water. We show that local structural ordering can be properly captured only by the structural descriptor ζ, but not by the other two descriptors particularly at a high temperature, where thermal noise effects are severe. The key difference of ζ from LSI and d5 is that only ζ considers H-bonding which is crucial to detect high translational and tetrahedral order of not only oxygen but also hydrogen atoms. The importance of H-bonding is very natural, considering the fact that the locally favored structures are stabilized by energy gain due to the formation of four hydrogen bonds between the central water molecule and its neighboring ones in the first shell. Our analysis of the water structure by using ζ strongly supports the two-state model of water: water is a dynamic mixture of locally favored (ordered) and normal-liquid (disordered) structures. This work demonstrates the importance of H-bonding in the characterization of water's structures and provides a useful structural descriptor for water-type tetrahedral liquids to study their structure and dynamics.

"Bildung", the Bologna Process and Kierkegaard's Concept of Subjective Thinking

ERIC Educational Resources Information Center

Reindal, Solveig M.

2013-01-01

The Bologna Framework for higher education has agreed on three "cycle descriptors"--knowledge, skill and general competence--which are to constitute the learning outcomes and credit ranges for the three cycles of higher education: The Bachelor, the Master and the PhD. In connection with the implementations of the national qualification…

Improving Student Achievement in a Multidisciplinary Context

ERIC Educational Resources Information Center

Chapman, Amanda; Bloxham, Sue

2004-01-01

This article analyses interim findings of an ongoing action research project into the use of assessment criteria and grade descriptors in the assessment process. The project is multidisciplinary and covers areas as diverse as Sports Sociology, Economics, Youth and Community Studies, and Education. The idea is to equip first-year students with the…

Descriptors for Law-Related Education.

ERIC Educational Resources Information Center

Wisconsin State Dept. of Public Instruction, Madison.

This guide provides a framework for developing a law-related curriculum in grades K-12. It is presented in nine major sections. Section I discusses the rationale for including law-related education in the curriculum. The rationale is that in order for citizens to make conscious choices, they must understand legal processes, reason through the need…

IT-benchmarking of clinical workflows: concept, implementation, and evaluation.

PubMed

Thye, Johannes; Straede, Matthias-Christopher; Liebe, Jan-David; Hübner, Ursula

2014-01-01

Due to the emerging evidence of health IT as opportunity and risk for clinical workflows, health IT must undergo a continuous measurement of its efficacy and efficiency. IT-benchmarks are a proven means for providing this information. The aim of this study was to enhance the methodology of an existing benchmarking procedure by including, in particular, new indicators of clinical workflows and by proposing new types of visualisation. Drawing on the concept of information logistics, we propose four workflow descriptors that were applied to four clinical processes. General and specific indicators were derived from these descriptors and processes. 199 chief information officers (CIOs) took part in the benchmarking. These hospitals were assigned to reference groups of a similar size and ownership from a total of 259 hospitals. Stepwise and comprehensive feedback was given to the CIOs. Most participants who evaluated the benchmark rated the procedure as very good, good, or rather good (98.4%). Benchmark information was used by CIOs for getting a general overview, advancing IT, preparing negotiations with board members, and arguing for a new IT project.

Investigations on the charge transfer mechanism at donor/acceptor interfaces in the quest for descriptors of organic solar cell performance.

PubMed

Muraoka, Azusa; Fujii, Mikiya; Mishima, Kenji; Matsunaga, Hiroki; Benten, Hiroaki; Ohkita, Hideo; Ito, Shinzaburo; Yamashita, Koichi

2018-05-07

Herein, we theoretically and experimentally investigated the mechanisms of charge separation processes of organic thin-film solar cells. PTB7, PTB1, and PTBF2 have been chosen as donors and PC 71 BM has been chosen as an acceptor considering that effective charge generation depends on the difference between the material combinations. Experimental results of transient absorption spectroscopy show that the hot process is a key step for determining external quantum efficiency (EQE) in these systems. From the quantum chemistry calculations, it has been found that EQE tends to increase as the transferred charge, charge transfer distance, and variation of dipole moments between the ground and excited states of the donor/acceptor complexes increase; this indicates that these physical quantities are a good descriptor to assess the donor-acceptor charge transfer quality contributing to the solar cell performance. We propose that designing donor/acceptor interfaces with large values of charge transfer distance and variation of dipole moments of the donor/acceptor complexes is a prerequisite for developing high-efficiency polymer/PCBM solar cells.

Protocol for audit of current Filipino practice in rehabilitation of stroke inpatients.

PubMed

Gonzalez-Suarez, Consuelo B; Dizon, Janine Margarita R; Grimmer, Karen; Estrada, Myrna S; Liao, Lauren Anne S; Malleta, Anne-Rochelle D; Tan, Ma Elena R; Marfil, Vero; Versales, Cristina S; Suarez, Jimah L; So, Kleon C; Uyehara, Edgardo D

2015-01-01

Stroke is one of the leading medical conditions in the Philippines. Over 500,000 Filipinos suffer from stroke annually. Provision of evidence-based medical and rehabilitation management for stroke patients has been a challenge due to existing environmental, social, and local health system issues. Thus, existing western guidelines on stroke rehabilitation were contextualized to draft recommendations relevant to the local Philippine setting. Prior to fully implementing the guidelines, an audit of current practice needs to be undertaken, thus the purpose of this audit protocol. A clinical audit of current practices in stroke rehabilitation in the Philippines will be undertaken. A consensus list of data items to be captured was identified by the audit team during a 2-day meeting in 2012. These items, including patient demographics, type of stroke, time to referral for rehabilitation management, length of hospital stay, and other relevant descriptors of stroke management were included as part of the audit. Hospitals in the Philippines will be recruited to take part in the audit activity. Recruitment will be via the registry of the Philippine Academy of Rehabilitation Medicine, where 90% of physiatrists (medical doctors specialized in rehabilitation medicine) are active members and are affiliated with various hospitals in the Philippines. Data collectors will be identified and trained in the audit process. A pilot audit will be conducted to test the feasibility of the audit protocol, and refinements to the protocol will be undertaken as necessary. The comprehensive audit process will take place for a period of 3 months. Data will be encoded using MS Excel(®). Data will be reported as means and percentages as appropriate. Subgroup analysis will be undertaken to look into differences and variability of stroke patient descriptors and rehabilitation activities. This audit study is an ambitious project, but given the "need" to conduct the audit to identify "gaps" in current practice, and the value it can bring to serve as a platform for implementation of evidence-based stroke management in the Philippines to achieve best patient and health outcomes, the audit team is more than ready to take up the challenge.

New formulae for Zagreb indices

NASA Astrophysics Data System (ADS)

Cangul, Ismail Naci; Yurttas, Aysun; Togan, Muge; Cevik, Ahmet Sinan

2017-07-01

In this paper, we study with some graph descriptors also called topological indices. These descriptors are useful in determination of some properties of chemical structures and preferred to some earlier descriptors as they are more practical. Especially the first and second Zagreb indices together with the first and second multiplicative Zagreb indices are considered and they are calculated in terms of the smallest and largest vertex degrees and vertex number for some well-known classes of graphs.

Analysis of A Drug Target-based Classification System using Molecular Descriptors.

PubMed

Lu, Jing; Zhang, Pin; Bi, Yi; Luo, Xiaomin

2016-01-01

Drug-target interaction is an important topic in drug discovery and drug repositioning. KEGG database offers a drug annotation and classification using a target-based classification system. In this study, we gave an investigation on five target-based classes: (I) G protein-coupled receptors; (II) Nuclear receptors; (III) Ion channels; (IV) Enzymes; (V) Pathogens, using molecular descriptors to represent each drug compound. Two popular feature selection methods, maximum relevance minimum redundancy and incremental feature selection, were adopted to extract the important descriptors. Meanwhile, an optimal prediction model based on nearest neighbor algorithm was constructed, which got the best result in identifying drug target-based classes. Finally, some key descriptors were discussed to uncover their important roles in the identification of drug-target classes.

A blur-invariant local feature for motion blurred image matching

NASA Astrophysics Data System (ADS)

Tong, Qiang; Aoki, Terumasa

2017-07-01

Image matching between a blurred (caused by camera motion, out of focus, etc.) image and a non-blurred image is a critical task for many image/video applications. However, most of the existing local feature schemes fail to achieve this work. This paper presents a blur-invariant descriptor and a novel local feature scheme including the descriptor and the interest point detector based on moment symmetry - the authors' previous work. The descriptor is based on a new concept - center peak moment-like element (CPME) which is robust to blur and boundary effect. Then by constructing CPMEs, the descriptor is also distinctive and suitable for image matching. Experimental results show our scheme outperforms state of the art methods for blurred image matching

Distribution of benthic macrofaunal communities in the western Baltic Sea with regard to near-bottom environmental parameters. 1. Causal analysis

NASA Astrophysics Data System (ADS)

Gogina, Mayya; Glockzin, Michael; Zettler, Michael L.

2010-01-01

In this study we relate patterns in the spatial distribution of macrofaunal communities to patterns in near-bottom environmental parameters, analysing the data observed in a limited area in the western Baltic Sea. The data used represents 208 stations, sampled during the years 2000 to 2007 simultaneously for benthic macrofauna, associated sediment and near-bottom environmental characteristics, in a depth range from 7.5 to 30 m. Only one degree of longitude wide, the study area is geographically bounded by the eastern part of the Mecklenburg Bight and the southwestern Darss Sill Area. Spatial distribution of benthic macrofauna is related to near-bottom environmental patterns by means of various statistical methods (e.g. rank correlation, hierarchical clustering, nMDS, BIO-ENV, CCA). Thus, key environmental descriptors were disclosed. Within the area of investigation, these were: water depth, regarded as a proxy for other environmental factors, and total organic content. Distinct benthic assemblages are defined and discriminated by particular species ( Hydrobia ulvae-Scoloplos armiger, Lagis koreni-Mysella bidentata and Capitella capitata-Halicryptus spinulosus). Each assemblage is related to different spatial subarea and characterised by a certain variability of environmental factors. This study represents a basis for the predictive modeling of species distribution in the selected study area.

Numeric promoter description - A comparative view on concepts and general application.

PubMed

Beier, Rico; Labudde, Dirk

2016-01-01

Nucleic acid molecules play a key role in a variety of biological processes. Starting from storage and transfer tasks, this also comprises the triggering of biological processes, regulatory effects and the active influence gained by target binding. Based on the experimental output (in this case promoter sequences), further in silico analyses aid in gaining new insights into these processes and interactions. The numerical description of nucleic acids thereby constitutes a bridge between the concrete biological issues and the analytical methods. Hence, this study compares 26 descriptor sets obtained by applying well-known numerical description concepts to an established dataset of 38 DNA promoter sequences. The suitability of the description sets was evaluated by computing partial least squares regression models and assessing the model accuracy. We conclude that the major importance regarding the descriptive power is attached to positional information rather than to explicitly incorporated physico-chemical information, since a sufficient amount of implicit physico-chemical information is already encoded in the nucleobase classification. The regression models especially benefited from employing the information that is encoded in the sequential and structural neighborhood of the nucleobases. Thus, the analyses of n-grams (short fragments of length n) suggested that they are valuable descriptors for DNA target interactions. A mixed n-gram descriptor set thereby yielded the best description of the promoter sequences. The corresponding regression model was checked and found to be plausible as it was able to reproduce the characteristic binding motifs of promoter sequences in a reasonable degree. As most functional nucleic acids are based on the principle of molecular recognition, the findings are not restricted to promoter sequences, but can rather be transferred to other kinds of functional nucleic acids. Thus, the concepts presented in this study could provide advantages for future nucleic acid-based technologies, like biosensoring, therapeutics and molecular imaging. Copyright © 2015 Elsevier Inc. All rights reserved.

Use of in Vitro HTS-Derived Concentration–Response Data as Biological Descriptors Improves the Accuracy of QSAR Models of in Vivo Toxicity

PubMed Central

Sedykh, Alexander; Zhu, Hao; Tang, Hao; Zhang, Liying; Richard, Ann; Rusyn, Ivan; Tropsha, Alexander

2011-01-01

Background Quantitative high-throughput screening (qHTS) assays are increasingly being used to inform chemical hazard identification. Hundreds of chemicals have been tested in dozens of cell lines across extensive concentration ranges by the National Toxicology Program in collaboration with the National Institutes of Health Chemical Genomics Center. Objectives Our goal was to test a hypothesis that dose–response data points of the qHTS assays can serve as biological descriptors of assayed chemicals and, when combined with conventional chemical descriptors, improve the accuracy of quantitative structure–activity relationship (QSAR) models applied to prediction of in vivo toxicity end points. Methods We obtained cell viability qHTS concentration–response data for 1,408 substances assayed in 13 cell lines from PubChem; for a subset of these compounds, rodent acute toxicity half-maximal lethal dose (LD50) data were also available. We used the k nearest neighbor classification and random forest QSAR methods to model LD50 data using chemical descriptors either alone (conventional models) or combined with biological descriptors derived from the concentration–response qHTS data (hybrid models). Critical to our approach was the use of a novel noise-filtering algorithm to treat qHTS data. Results Both the external classification accuracy and coverage (i.e., fraction of compounds in the external set that fall within the applicability domain) of the hybrid QSAR models were superior to conventional models. Conclusions Concentration–response qHTS data may serve as informative biological descriptors of molecules that, when combined with conventional chemical descriptors, may considerably improve the accuracy and utility of computational approaches for predicting in vivo animal toxicity end points. PMID:20980217

Toxicity prediction of ionic liquids based on Daphnia magna by using density functional theory

NASA Astrophysics Data System (ADS)

Nu’aim, M. N.; Bustam, M. A.

2018-04-01

By using a model called density functional theory, the toxicity of ionic liquids can be predicted and forecast. It is a theory that allowing the researcher to have a substantial tool for computation of the quantum state of atoms, molecules and solids, and molecular dynamics which also known as computer simulation method. It can be done by using structural feature based quantum chemical reactivity descriptor. The identification of ionic liquids and its Log[EC50] data are from literature data that available in Ismail Hossain thesis entitled “Synthesis, Characterization and Quantitative Structure Toxicity Relationship of Imidazolium, Pyridinium and Ammonium Based Ionic Liquids”. Each cation and anion of the ionic liquids were optimized and calculated. The geometry optimization and calculation from the software, produce the value of highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO). From the value of HOMO and LUMO, the value for other toxicity descriptors were obtained according to their formulas. The toxicity descriptor that involves are electrophilicity index, HOMO, LUMO, energy gap, chemical potential, hardness and electronegativity. The interrelation between the descriptors are being determined by using a multiple linear regression (MLR). From this MLR, all descriptors being analyzed and the descriptors that are significant were chosen. In order to develop the finest model equation for toxicity prediction of ionic liquids, the selected descriptors that are significant were used. The validation of model equation was performed with the Log[EC50] data from the literature and the final model equation was developed. A bigger range of ionic liquids which nearly 108 of ionic liquids can be predicted from this model equation.

Structural protein descriptors in 1-dimension and their sequence-based predictions.

PubMed

Kurgan, Lukasz; Disfani, Fatemeh Miri

2011-09-01

The last few decades observed an increasing interest in development and application of 1-dimensional (1D) descriptors of protein structure. These descriptors project 3D structural features onto 1D strings of residue-wise structural assignments. They cover a wide-range of structural aspects including conformation of the backbone, burying depth/solvent exposure and flexibility of residues, and inter-chain residue-residue contacts. We perform first-of-its-kind comprehensive comparative review of the existing 1D structural descriptors. We define, review and categorize ten structural descriptors and we also describe, summarize and contrast over eighty computational models that are used to predict these descriptors from the protein sequences. We show that the majority of the recent sequence-based predictors utilize machine learning models, with the most popular being neural networks, support vector machines, hidden Markov models, and support vector and linear regressions. These methods provide high-throughput predictions and most of them are accessible to a non-expert user via web servers and/or stand-alone software packages. We empirically evaluate several recent sequence-based predictors of secondary structure, disorder, and solvent accessibility descriptors using a benchmark set based on CASP8 targets. Our analysis shows that the secondary structure can be predicted with over 80% accuracy and segment overlap (SOV), disorder with over 0.9 AUC, 0.6 Matthews Correlation Coefficient (MCC), and 75% SOV, and relative solvent accessibility with PCC of 0.7 and MCC of 0.6 (0.86 when homology is used). We demonstrate that the secondary structure predicted from sequence without the use of homology modeling is as good as the structure extracted from the 3D folds predicted by top-performing template-based methods.

3D face analysis by using Mesh-LBP feature

NASA Astrophysics Data System (ADS)

Wang, Haoyu; Yang, Fumeng; Zhang, Yuming; Wu, Congzhong

2017-11-01

Objective: Face Recognition is one of the widely application of image processing. Corresponding two-dimensional limitations, such as the pose and illumination changes, to a certain extent restricted its accurate rate and further development. How to overcome the pose and illumination changes and the effects of self-occlusion is the research hotspot and difficulty, also attracting more and more domestic and foreign experts and scholars to study it. 3D face recognition fusing shape and texture descriptors has become a very promising research direction. Method: Our paper presents a 3D point cloud based on mesh local binary pattern grid (Mesh-LBP), then feature extraction for 3D face recognition by fusing shape and texture descriptors. 3D Mesh-LBP not only retains the integrity of the 3D geometry, is also reduces the need for recognition process of normalization steps, because the triangle Mesh-LBP descriptor is calculated on 3D grid. On the other hand, in view of multi-modal consistency in face recognition advantage, construction of LBP can fusing shape and texture information on Triangular Mesh. In this paper, some of the operators used to extract Mesh-LBP, Such as the normal vectors of the triangle each face and vertex, the gaussian curvature, the mean curvature, laplace operator and so on. Conclusion: First, Kinect devices obtain 3D point cloud face, after the pretreatment and normalization, then transform it into triangular grid, grid local binary pattern feature extraction from face key significant parts of face. For each local face, calculate its Mesh-LBP feature with Gaussian curvature, mean curvature laplace operator and so on. Experiments on the our research database, change the method is robust and high recognition accuracy.

Information-theoretic signatures of biodiversity in the barcoding gene.

PubMed

Barbosa, Valmir C

2018-08-14

Analyzing the information content of DNA, though holding the promise to help quantify how the processes of evolution have led to information gain throughout the ages, has remained an elusive goal. Paradoxically, one of the main reasons for this has been precisely the great diversity of life on the planet: if on the one hand this diversity is a rich source of data for information-content analysis, on the other hand there is so much variation as to make the task unmanageable. During the past decade or so, however, succinct fragments of the COI mitochondrial gene, which is present in all animal phyla and in a few others, have been shown to be useful for species identification through DNA barcoding. A few million such fragments are now publicly available through the BOLD systems initiative, thus providing an unprecedented opportunity for relatively comprehensive information-theoretic analyses of DNA to be attempted. Here we show how a generalized form of total correlation can yield distinctive information-theoretic descriptors of the phyla represented in those fragments. In order to illustrate the potential of this analysis to provide new insight into the evolution of species, we performed principal component analysis on standardized versions of the said descriptors for 23 phyla. Surprisingly, we found that, though based solely on the species represented in the data, the first principal component correlates strongly with the natural logarithm of the number of all known living species for those phyla. The new descriptors thus constitute clear information-theoretic signatures of the processes whereby evolution has given rise to current biodiversity, which suggests their potential usefulness in further related studies. Copyright © 2018 Elsevier Ltd. All rights reserved.

Towards the chemometric dissection of peptide - HLA-A*0201 binding affinity: comparison of local and global QSAR models

NASA Astrophysics Data System (ADS)

Doytchinova, Irini A.; Walshe, Valerie; Borrow, Persephone; Flower, Darren R.

2005-03-01

The affinities of 177 nonameric peptides binding to the HLA-A*0201 molecule were measured using a FACS-based MHC stabilisation assay and analysed using chemometrics. Their structures were described by global and local descriptors, QSAR models were derived by genetic algorithm, stepwise regression and PLS. The global molecular descriptors included molecular connectivity χ indices, κ shape indices, E-state indices, molecular properties like molecular weight and log P, and three-dimensional descriptors like polarizability, surface area and volume. The local descriptors were of two types. The first used a binary string to indicate the presence of each amino acid type at each position of the peptide. The second was also position-dependent but used five z-scales to describe the main physicochemical properties of the amino acids forming the peptides. The models were developed using a representative training set of 131 peptides and validated using an independent test set of 46 peptides. It was found that the global descriptors could not explain the variance in the training set nor predict the affinities of the test set accurately. Both types of local descriptors gave QSAR models with better explained variance and predictive ability. The results suggest that, in their interactions with the MHC molecule, the peptide acts as a complicated ensemble of multiple amino acids mutually potentiating each other.

3D molecular descriptors important for clinical success.

PubMed

Kombo, David C; Tallapragada, Kartik; Jain, Rachit; Chewning, Joseph; Mazurov, Anatoly A; Speake, Jason D; Hauser, Terry A; Toler, Steve

2013-02-25

The pharmacokinetic and safety profiles of clinical drug candidates are greatly influenced by their requisite physicochemical properties. In particular, it has been shown that 2D molecular descriptors such as fraction of Sp3 carbon atoms (Fsp3) and number of stereo centers correlate with clinical success. Using the proteomic off-target hit rate of nicotinic ligands, we found that shape-based 3D descriptors such as the radius of gyration and shadow indices discriminate off-target promiscuity better than do Fsp3 and the number of stereo centers. We have deduced the relevant descriptor values required for a ligand to be nonpromiscuous. Investigating the MDL Drug Data Report (MDDR) database as compounds move from the preclinical stage toward the market, we have found that these shape-based 3D descriptors predict clinical success of compounds at preclinical and phase1 stages vs compounds withdrawn from the market better than do Fsp3 and LogD. Further, these computed 3D molecular descriptors correlate well with experimentally observed solubility, which is among well-known physicochemical properties that drive clinical success. We also found that about 84% of launched drugs satisfy either Shadow index or Fsp3 criteria, whereas withdrawn and discontinued compounds fail to meet the same criteria. Our studies suggest that spherical compounds (rather than their elongated counterparts) with a minimal number of aromatic rings may exhibit a high propensity to advance from clinical trials to market.

Influence of Texture and Colour in Breast TMA Classification

PubMed Central

Fernández-Carrobles, M. Milagro; Bueno, Gloria; Déniz, Oscar; Salido, Jesús; García-Rojo, Marcial; González-López, Lucía

2015-01-01

Breast cancer diagnosis is still done by observation of biopsies under the microscope. The development of automated methods for breast TMA classification would reduce diagnostic time. This paper is a step towards the solution for this problem and shows a complete study of breast TMA classification based on colour models and texture descriptors. The TMA images were divided into four classes: i) benign stromal tissue with cellularity, ii) adipose tissue, iii) benign and benign anomalous structures, and iv) ductal and lobular carcinomas. A relevant set of features was obtained on eight different colour models from first and second order Haralick statistical descriptors obtained from the intensity image, Fourier, Wavelets, Multiresolution Gabor, M-LBP and textons descriptors. Furthermore, four types of classification experiments were performed using six different classifiers: (1) classification per colour model individually, (2) classification by combination of colour models, (3) classification by combination of colour models and descriptors, and (4) classification by combination of colour models and descriptors with a previous feature set reduction. The best result shows an average of 99.05% accuracy and 98.34% positive predictive value. These results have been obtained by means of a bagging tree classifier with combination of six colour models and the use of 1719 non-correlated (correlation threshold of 97%) textural features based on Statistical, M-LBP, Gabor and Spatial textons descriptors. PMID:26513238

Stargate GTM: Bridging Descriptor and Activity Spaces.

PubMed

Gaspar, Héléna A; Baskin, Igor I; Marcou, Gilles; Horvath, Dragos; Varnek, Alexandre

2015-11-23

Predicting the activity profile of a molecule or discovering structures possessing a specific activity profile are two important goals in chemoinformatics, which could be achieved by bridging activity and molecular descriptor spaces. In this paper, we introduce the "Stargate" version of the Generative Topographic Mapping approach (S-GTM) in which two different multidimensional spaces (e.g., structural descriptor space and activity space) are linked through a common 2D latent space. In the S-GTM algorithm, the manifolds are trained simultaneously in two initial spaces using the probabilities in the 2D latent space calculated as a weighted geometric mean of probability distributions in both spaces. S-GTM has the following interesting features: (1) activities are involved during the training procedure; therefore, the method is supervised, unlike conventional GTM; (2) using molecular descriptors of a given compound as input, the model predicts a whole activity profile, and (3) using an activity profile as input, areas populated by relevant chemical structures can be detected. To assess the performance of S-GTM prediction models, a descriptor space (ISIDA descriptors) of a set of 1325 GPCR ligands was related to a B-dimensional (B = 1 or 8) activity space corresponding to pKi values for eight different targets. S-GTM outperforms conventional GTM for individual activities and performs similarly to the Lasso multitask learning algorithm, although it is still slightly less accurate than the Random Forest method.

QSPR study of polychlorinated diphenyl ethers by molecular electronegativity distance vector (MEDV-4).

PubMed

Sun, Lili; Zhou, Liping; Yu, Yu; Lan, Yukun; Li, Zhiliang

2007-01-01

Polychlorinated diphenyl ethers (PCDEs) have received more and more concerns as a group of ubiquitous potential persistent organic pollutants (POPs). By using molecular electronegativity distance vector (MEDV-4), multiple linear regression (MLR) models are developed for sub-cooled liquid vapor pressures (P(L)), n-octanol/water partition coefficients (K(OW)) and sub-cooled liquid water solubilities (S(W,L)) of 209 PCDEs and diphenyl ether. The correlation coefficients (R) and the leave-one-out cross-validation (LOO) correlation coefficients (R(CV)) of all the 6-descriptor models for logP(L), logK(OW) and logS(W,L) are more than 0.98. By using stepwise multiple regression (SMR), the descriptors are selected and the resulting models are 5-descriptor model for logP(L), 4-descriptor model for logK(OW), and 6-descriptor model for logS(W,L), respectively. All these models exhibit excellent estimate capabilities for internal sample set and good predictive capabilities for external samples set. The consistency between observed and estimated/predicted values for logP(L) is the best (R=0.996, R(CV)=0.996), followed by logK(OW) (R=0.992, R(CV)=0.992) and logS(W,L) (R=0.983, R(CV)=0.980). By using MEDV-4 descriptors, the QSPR models can be used for prediction and the model predictions can hence extend the current database of experimental values.

A quantitative structure-activity relationship to predict efficacy of granular activated carbon adsorption to control emerging contaminants.

PubMed

Kennicutt, A R; Morkowchuk, L; Krein, M; Breneman, C M; Kilduff, J E

2016-08-01

A quantitative structure-activity relationship was developed to predict the efficacy of carbon adsorption as a control technology for endocrine-disrupting compounds, pharmaceuticals, and components of personal care products, as a tool for water quality professionals to protect public health. Here, we expand previous work to investigate a broad spectrum of molecular descriptors including subdivided surface areas, adjacency and distance matrix descriptors, electrostatic partial charges, potential energy descriptors, conformation-dependent charge descriptors, and Transferable Atom Equivalent (TAE) descriptors that characterize the regional electronic properties of molecules. We compare the efficacy of linear (Partial Least Squares) and non-linear (Support Vector Machine) machine learning methods to describe a broad chemical space and produce a user-friendly model. We employ cross-validation, y-scrambling, and external validation for quality control. The recommended Support Vector Machine model trained on 95 compounds having 23 descriptors offered a good balance between good performance statistics, low error, and low probability of over-fitting while describing a wide range of chemical features. The cross-validated model using a log-uptake (qe) response calculated at an aqueous equilibrium concentration (Ce) of 1 μM described the training dataset with an r(2) of 0.932, had a cross-validated r(2) of 0.833, and an average residual of 0.14 log units.

Uniting Cheminformatics and Chemical Theory To Predict the Intrinsic Aqueous Solubility of Crystalline Druglike Molecules

PubMed Central

2014-01-01

We present four models of solution free-energy prediction for druglike molecules utilizing cheminformatics descriptors and theoretically calculated thermodynamic values. We make predictions of solution free energy using physics-based theory alone and using machine learning/quantitative structure–property relationship (QSPR) models. We also develop machine learning models where the theoretical energies and cheminformatics descriptors are used as combined input. These models are used to predict solvation free energy. While direct theoretical calculation does not give accurate results in this approach, machine learning is able to give predictions with a root mean squared error (RMSE) of ∼1.1 log S units in a 10-fold cross-validation for our Drug-Like-Solubility-100 (DLS-100) dataset of 100 druglike molecules. We find that a model built using energy terms from our theoretical methodology as descriptors is marginally less predictive than one built on Chemistry Development Kit (CDK) descriptors. Combining both sets of descriptors allows a further but very modest improvement in the predictions. However, in some cases, this is a statistically significant enhancement. These results suggest that there is little complementarity between the chemical information provided by these two sets of descriptors, despite their different sources and methods of calculation. Our machine learning models are also able to predict the well-known Solubility Challenge dataset with an RMSE value of 0.9–1.0 log S units. PMID:24564264

Embedding ecosystem services into the Marine Strategy Framework Directive: Illustrated by eutrophication in the North Sea

NASA Astrophysics Data System (ADS)

O'Higgins, T. G.; Gilbert, A. J.

2014-03-01

The introduction of the Marine Strategy Framework Directive (MSFD) with its focus on an Ecosystem Approach places an emphasis on the human dimensions of environmental problems. Human activities may be the source of marine degradation, but may also be adversely affected should degradation compromise the provision of ecosystem services. The MSFD marks a shift away from management aiming to restore past, undegraded states toward management for Good Environmental Status (GEnS) based on delivery of marine goods and services. An example relating ecosystem services to criteria for Good Environmental Status is presented for eutrophication, a long recognised problem in many parts of Europe's seas and specifically targeted by descriptors for GEnS. Taking the North Sea as a case study the relationships between the eutrophication criteria of the MSFD and final and intermediate marine ecosystem services are examined. Ecosystem services are valued, where possible in monetary terms, in order to illustrate how eutrophication affects human welfare (economic externalities) through its multiple effects on ecosystem services.

Concordance between macrophytes and macroinvertebrates in a Mediterranean river of central Apennine region.

PubMed

Traversetti, Lorenzo; Scalici, Massimiliano; Ginepri, Valeria; Manfrin, Alessandro; Ceschin, Simona

2014-05-01

The main aim of this study was to improve the knowledge about the concordance among macrophytes and macroinvertebrates to provide complementary information and facilitate the procedures for quality assessment of river ecosystems. Macrophytes and macroinvertebrates were collected in 11 sampling sites along a central Apennine calcareous river in October 2008 and June 2009. The concordance between the two biomonitoring groups was tested according to several environmental parameters. The comparison of data matrix similarities by Mantel test showed differences in the assemblage of macrophytes and macroinvertebrates along the river since correlation values were 0.04, p > 0.05 in October 2008 and 0.39, p > 0.05 in June 2009. The study revealed lack of concordance between the two groups, emphasizing that the information provided by macrophytes and macroinvertebrates does not overlap in terms of response to environmental parameters. Indeed, the two different biological groups resulted useful descriptors of different parameters. Together, they could represent a complementary tool to reflect the river environmental quality.

Estimation of descriptors for hydrogen-bonding compounds from chromatographic and liquid-liquid partition measurements.

PubMed

Lenca, Nicole; Atapattu, Sanka N; Poole, Colin F

2017-12-01

Retention factors obtained by gas chromatography and reversed-phase liquid chromatography on varied columns and partition constants in different liquid-liquid partition systems are used to estimate WSU descriptor values for 36 anilines and N-heterocyclic compounds, 13 amides and related compounds, and 45 phenols and alcohols. These compounds are suitable for use as calibration compounds to characterize separation systems covering the descriptor space E=0.2-3, S=0.4-2.1, A=0-1.5, B=0.1-1.5, L=2.5-10.0 and V=0.5-2.2. Hydrogen-bonding properties are discussed in terms of structure, the possibility of induction effects, intramolecular hydrogen bonding and steric factors for anilines, amides, phenols and alcohols. The relationship between these parameters and observed descriptor values are difficult to predict from structure but facilitate improving the general occupancy of the descriptor space by creating incremental changes in hydrogen-bonding properties. It is verified that the compounds included in this study can be merged with an existing database of compounds recommended for characterizing separation systems. Copyright © 2017 Elsevier B.V. All rights reserved.

Locator-Checker-Scaler Object Tracking Using Spatially Ordered and Weighted Patch Descriptor.

PubMed

Kim, Han-Ul; Kim, Chang-Su

2017-08-01

In this paper, we propose a simple yet effective object descriptor and a novel tracking algorithm to track a target object accurately. For the object description, we divide the bounding box of a target object into multiple patches and describe them with color and gradient histograms. Then, we determine the foreground weight of each patch to alleviate the impacts of background information in the bounding box. To this end, we perform random walk with restart (RWR) simulation. We then concatenate the weighted patch descriptors to yield the spatially ordered and weighted patch (SOWP) descriptor. For the object tracking, we incorporate the proposed SOWP descriptor into a novel tracking algorithm, which has three components: locator, checker, and scaler (LCS). The locator and the scaler estimate the center location and the size of a target, respectively. The checker determines whether it is safe to adjust the target scale in a current frame. These three components cooperate with one another to achieve robust tracking. Experimental results demonstrate that the proposed LCS tracker achieves excellent performance on recent benchmarks.

Quantum descriptors for predictive toxicology of halogenated aliphatic hydrocarbons.

PubMed

Trohalaki, S; Pachter, R

2003-04-01

In order to improve Quantitative Structure-Activity Relationships (QSARs) for halogenated aliphatics (HA) and to better understand the biophysical mechanism of toxic response to these ubiquitous chemicals, we employ improved quantum-mechanical descriptors to account for HA electrophilicity. We demonstrate that, unlike the lowest unoccupied molecular orbital energy, ELUMO, which was previously used as a descriptor, the electron affinity can be systematically improved by application of higher levels of theory. We also show that employing the reciprocal of ELUMO, which is more consistent with frontier molecular orbital (FMO) theory, improves the correlations with in vitro toxicity data. We offer explanations based on FMO theory for a result from our previous work, in which the LUMO energies of HA anions correlated surprisingly well with in vitro toxicity data. Additional descriptors are also suggested and interpreted in terms of the accepted biophysical mechanism of toxic response to HAs and new QSARs are derived for various chemical categories that compose the data set employed. These alternate descriptors provide important insight and could benefit other classes of compounds where the biophysical mechanism of toxic response involves dissociative attachment.

Artificial Intelligence Methods Applied to Parameter Detection of Atrial Fibrillation

NASA Astrophysics Data System (ADS)

Arotaritei, D.; Rotariu, C.

2015-09-01

In this paper we present a novel method to develop an atrial fibrillation (AF) based on statistical descriptors and hybrid neuro-fuzzy and crisp system. The inference of system produce rules of type if-then-else that care extracted to construct a binary decision system: normal of atrial fibrillation. We use TPR (Turning Point Ratio), SE (Shannon Entropy) and RMSSD (Root Mean Square of Successive Differences) along with a new descriptor, Teager- Kaiser energy, in order to improve the accuracy of detection. The descriptors are calculated over a sliding window that produce very large number of vectors (massive dataset) used by classifier. The length of window is a crisp descriptor meanwhile the rest of descriptors are interval-valued type. The parameters of hybrid system are adapted using Genetic Algorithm (GA) algorithm with fitness single objective target: highest values for sensibility and sensitivity. The rules are extracted and they are part of the decision system. The proposed method was tested using the Physionet MIT-BIH Atrial Fibrillation Database and the experimental results revealed a good accuracy of AF detection in terms of sensitivity and specificity (above 90%).

Learning moment-based fast local binary descriptor

NASA Astrophysics Data System (ADS)

Bellarbi, Abdelkader; Zenati, Nadia; Otmane, Samir; Belghit, Hayet

2017-03-01

Recently, binary descriptors have attracted significant attention due to their speed and low memory consumption; however, using intensity differences to calculate the binary descriptive vector is not efficient enough. We propose an approach to binary description called POLAR_MOBIL, in which we perform binary tests between geometrical and statistical information using moments in the patch instead of the classical intensity binary test. In addition, we introduce a learning technique used to select an optimized set of binary tests with low correlation and high variance. This approach offers high distinctiveness against affine transformations and appearance changes. An extensive evaluation on well-known benchmark datasets reveals the robustness and the effectiveness of the proposed descriptor, as well as its good performance in terms of low computation complexity when compared with state-of-the-art real-time local descriptors.

A Fully Automated Method to Detect and Segment a Manufactured Object in an Underwater Color Image

NASA Astrophysics Data System (ADS)

Barat, Christian; Phlypo, Ronald

2010-12-01

We propose a fully automated active contours-based method for the detection and the segmentation of a moored manufactured object in an underwater image. Detection of objects in underwater images is difficult due to the variable lighting conditions and shadows on the object. The proposed technique is based on the information contained in the color maps and uses the visual attention method, combined with a statistical approach for the detection and an active contour for the segmentation of the object to overcome the above problems. In the classical active contour method the region descriptor is fixed and the convergence of the method depends on the initialization. With our approach, this dependence is overcome with an initialization using the visual attention results and a criterion to select the best region descriptor. This approach improves the convergence and the processing time while providing the advantages of a fully automated method.

A novel knowledge-based system for interpreting complex engineering drawings: theory, representation, and implementation.

PubMed

Lu, Tong; Tai, Chiew-Lan; Yang, Huafei; Cai, Shijie

2009-08-01

We present a novel knowledge-based system to automatically convert real-life engineering drawings to content-oriented high-level descriptions. The proposed method essentially turns the complex interpretation process into two parts: knowledge representation and knowledge-based interpretation. We propose a new hierarchical descriptor-based knowledge representation method to organize the various types of engineering objects and their complex high-level relations. The descriptors are defined using an Extended Backus Naur Form (EBNF), facilitating modification and maintenance. When interpreting a set of related engineering drawings, the knowledge-based interpretation system first constructs an EBNF-tree from the knowledge representation file, then searches for potential engineering objects guided by a depth-first order of the nodes in the EBNF-tree. Experimental results and comparisons with other interpretation systems demonstrate that our knowledge-based system is accurate and robust for high-level interpretation of complex real-life engineering projects.

Multiple feature fusion via covariance matrix for visual tracking

NASA Astrophysics Data System (ADS)

Jin, Zefenfen; Hou, Zhiqiang; Yu, Wangsheng; Wang, Xin; Sun, Hui

2018-04-01

Aiming at the problem of complicated dynamic scenes in visual target tracking, a multi-feature fusion tracking algorithm based on covariance matrix is proposed to improve the robustness of the tracking algorithm. In the frame-work of quantum genetic algorithm, this paper uses the region covariance descriptor to fuse the color, edge and texture features. It also uses a fast covariance intersection algorithm to update the model. The low dimension of region covariance descriptor, the fast convergence speed and strong global optimization ability of quantum genetic algorithm, and the fast computation of fast covariance intersection algorithm are used to improve the computational efficiency of fusion, matching, and updating process, so that the algorithm achieves a fast and effective multi-feature fusion tracking. The experiments prove that the proposed algorithm can not only achieve fast and robust tracking but also effectively handle interference of occlusion, rotation, deformation, motion blur and so on.

Mineral and sensory profile of seasoned cracked olives packed in diverse salt mixtures.

PubMed

Moreno-Baquero, J M; Bautista-Gallego, J; Garrido-Fernández, A; López-López, A

2013-05-01

This work studies the effect of packing cracked seasoned olives with NaCl, KCl, and CaCl(2) mixture brines on their mineral nutrients and sensory attributes, using RSM methodology. The Na, K, Ca, and residual natural Mn contents in flesh as well as saltiness, bitterness and fibrousness were significantly related to the initial concentrations of salts in the packing solution. This new process led to table olives with a significantly lower sodium content (about 31%) than the traditional product but fortified in K and Ca. High levels of Na and Ca in the flesh led to high scores of acidity and saltiness (the first descriptor) and bitterness (the second) while the K content was unrelated to any sensory descriptor. The new presentations using moderate proportions of alternative salts will therefore have improved nutritional value and healthier characteristics but only a slightly modified sensory profile. Copyright © 2012 Elsevier Ltd. All rights reserved.

Using multi-terminology indexing for the assignment of MeSH descriptors to health resources in a French online catalogue.

PubMed

Pereira, Suzanne; Névéol, Aurélie; Kerdelhué, Gaétan; Serrot, Elisabeth; Joubert, Michel; Darmoni, Stéfan J

2008-11-06

To assist with the development of a French online quality-controlled health gateway(CISMeF), an automatic indexing tool assigning MeSH descriptors to medical text in French was created. The French Multi-Terminology Indexer (FMTI) relies on a multi-terminology approach involving four prominent medical terminologies and the mappings between them. In this paper,we compare lemmatization and stemming as methods to process French medical text for indexing. We also evaluate the multi-terminology approach implemented in F-MTI. The indexing strategies were assessed on a corpus of 18,814 resources indexed manually. There is little difference in the indexing performance when lemmatization or stemming is used. However, the multi-terminology approach outperforms indexing relying on a single terminology in terms of recall. F-MTI will soon be used in the CISMeF production environment and in a Health MultiTerminology Server in French.

A method for real-time implementation of HOG feature extraction

NASA Astrophysics Data System (ADS)

Luo, Hai-bo; Yu, Xin-rong; Liu, Hong-mei; Ding, Qing-hai

2011-08-01

Histogram of oriented gradient (HOG) is an efficient feature extraction scheme, and HOG descriptors are feature descriptors which is widely used in computer vision and image processing for the purpose of biometrics, target tracking, automatic target detection(ATD) and automatic target recognition(ATR) etc. However, computation of HOG feature extraction is unsuitable for hardware implementation since it includes complicated operations. In this paper, the optimal design method and theory frame for real-time HOG feature extraction based on FPGA were proposed. The main principle is as follows: firstly, the parallel gradient computing unit circuit based on parallel pipeline structure was designed. Secondly, the calculation of arctangent and square root operation was simplified. Finally, a histogram generator based on parallel pipeline structure was designed to calculate the histogram of each sub-region. Experimental results showed that the HOG extraction can be implemented in a pixel period by these computing units.

Classification of facial-emotion expression in the application of psychotherapy using Viola-Jones and Edge-Histogram of Oriented Gradient.

PubMed

Candra, Henry; Yuwono, Mitchell; Rifai Chai; Nguyen, Hung T; Su, Steven

2016-08-01

Psychotherapy requires appropriate recognition of patient's facial-emotion expression to provide proper treatment in psychotherapy session. To address the needs this paper proposed a facial emotion recognition system using Combination of Viola-Jones detector together with a feature descriptor we term Edge-Histogram of Oriented Gradients (E-HOG). The performance of the proposed method is compared with various feature sources including the face, the eyes, the mouth, as well as both the eyes and the mouth. Seven classes of basic emotions have been successfully identified with 96.4% accuracy using Multi-class Support Vector Machine (SVM). The proposed descriptor E-HOG is much leaner to compute compared to traditional HOG as shown by a significant improvement in processing time as high as 1833.33% (p-value = 2.43E-17) with a slight reduction in accuracy of only 1.17% (p-value = 0.0016).

Improving Zernike moments comparison for optimal similarity and rotation angle retrieval.

PubMed

Revaud, Jérôme; Lavoué, Guillaume; Baskurt, Atilla

2009-04-01

Zernike moments constitute a powerful shape descriptor in terms of robustness and description capability. However the classical way of comparing two Zernike descriptors only takes into account the magnitude of the moments and loses the phase information. The novelty of our approach is to take advantage of the phase information in the comparison process while still preserving the invariance to rotation. This new Zernike comparator provides a more accurate similarity measure together with the optimal rotation angle between the patterns, while keeping the same complexity as the classical approach. This angle information is particularly of interest for many applications, including 3D scene understanding through images. Experiments demonstrate that our comparator outperforms the classical one in terms of similarity measure. In particular the robustness of the retrieval against noise and geometric deformation is greatly improved. Moreover, the rotation angle estimation is also more accurate than state-of-the-art algorithms.

Sensory shelf-life limiting factor of high hydrostatic pressure processed avocado paste.

PubMed

Jacobo-Velázquez, D A; Hernández-Brenes, C

2011-08-01

High hydrostatic pressure (HHP) processing pasteurizes avocado paste without a significant impact on flavor. Although HHP-treated avocado paste stored under refrigeration is safe for human consumption for months, sensory changes taking place during storage cause the rejection of the product by consumers within days. Although it is known that the shelf life of the product ends before its microbial counts are high, its sensory shelf life limiting factor remains unknown. The present study focused on the use of a trained panel and a consumer panel to determine the sensory shelf life limiting factor of HHP-treated avocado paste. The trained panel identified sour and rancid flavors as the main sensory descriptors (critical descriptors) that differentiated stored from freshly processed samples. Further data obtained from consumers identified sour flavor as the main cause for a significant decrease in the acceptability (shelf life limiting factor) of refrigerated HHP-treated avocado paste. The study allowed the elucidation of a proposed deterioration mechanism for HHP-treated avocado paste during its refrigerated shelf life. The information through this work enhances scientific knowledge of the product and proposes the sour flavor development during storage as a relevant sensory attribute that needs to be improved in order to enhance the product shelf life. At present, HHP is the most effective commercial nonthermal technology to process avocado paste when compared to thermal and chemical alternatives. HHP-treated avocado paste is a microbiologically stable food for a period of at least 45 d stored under refrigeration. However, previous published work indicated that consumers rejected the product after approximately 19 d of storage due to sensory changes. This manuscript presents a sensory study that permitted the identification of the critical sensory descriptor that is acting as the sensory shelf life limiting factor of the product. The data presented herein along with previous reported data allows a better understanding of the deterioration mechanism that occurs during the storage of HHP-treated avocado paste. This information is relevant and useful for the elucidation of possible alternatives to enhance the shelf life of HHP-treated avocado paste. © 2011 Institute of Food Technologists®

A Validation Study of the Adolescent Dissociative Experiences Scale

ERIC Educational Resources Information Center

Keck Seeley, Susan. M.; Perosa, Sandra, L.; Perosa, Linda, M.

2004-01-01

Objective: The purpose of this study was to further the validation process of the Adolescent Dissociative Experiences Scale (A-DES). In this study, a 6-item Likert response format with descriptors was used when responding to the A-DES rather than the 11-item response format used in the original A-DES. Method: The internal reliability and construct…

Application of the QSPR approach to the boiling points of azeotropes.

PubMed

Katritzky, Alan R; Stoyanova-Slavova, Iva B; Tämm, Kaido; Tamm, Tarmo; Karelson, Mati

2011-04-21

CODESSA Pro derivative descriptors were calculated for a data set of 426 azeotropic mixtures by the centroid approximation and the weighted-contribution-factor approximation. The two approximations produced almost identical four-descriptor QSPR models relating the structural characteristic of the individual components of azeotropes to the azeotropic boiling points. These models were supported by internal and external validations. The descriptors contributing to the QSPR models are directly related to the three components of the enthalpy (heat) of vaporization.

TOXICO-CHEMINFORMATICS AND QSAR MODELING OF ...

EPA Pesticide Factsheets

This abstract concludes that QSAR approaches combined with toxico-chemoinformatics descriptors can enhance predictive toxicology models. This abstract concludes that QSAR approaches combined with toxico-chemoinformatics descriptors can enhance predictive toxicology models.

Where the bugs are: analyzing distributions of bacterial phyla by descriptor keyword search in the nucleotide database.

PubMed

Squartini, Andrea

2011-07-26

The associations between bacteria and environment underlie their preferential interactions with given physical or chemical conditions. Microbial ecology aims at extracting conserved patterns of occurrence of bacterial taxa in relation to defined habitats and contexts. In the present report the NCBI nucleotide sequence database is used as dataset to extract information relative to the distribution of each of the 24 phyla of the bacteria superkingdom and of the Archaea. Over two and a half million records are filtered in their cross-association with each of 48 sets of keywords, defined to cover natural or artificial habitats, interactions with plant, animal or human hosts, and physical-chemical conditions. The results are processed showing: (a) how the different descriptors enrich or deplete the proportions at which the phyla occur in the total database; (b) in which order of abundance do the different keywords score for each phylum (preferred habitats or conditions), and to which extent are phyla clustered to few descriptors (specific) or spread across many (cosmopolitan); (c) which keywords individuate the communities ranking highest for diversity and evenness. A number of cues emerge from the results, contributing to sharpen the picture on the functional systematic diversity of prokaryotes. Suggestions are given for a future automated service dedicated to refining and updating such kind of analyses via public bioinformatic engines.

Sensory description of marine oils through development of a sensory wheel and vocabulary.

PubMed

Larssen, W E; Monteleone, E; Hersleth, M

2018-04-01

The Omega-3 industry lacks a defined methodology and a vocabulary for evaluating the sensory quality of marine oils. This study was conducted to identify the sensory descriptors of marine oils and organize them in a sensory wheel for use as a tool in quality assessment. Samples of marine oils were collected from six of the largest producers of omega-3 products in Norway. The oils were selected to cover as much variation in sensory characteristics as possible, i.e. oils with different fatty acid content originating from different species. Oils were evaluated by six industry expert panels and one trained sensory panel to build up a vocabulary through a series of language sessions. A total of 184 aroma (odor by nose), flavor, taste and mouthfeel descriptors were generated. A sensory wheel based on 60 selected descriptors grouped together in 21 defined categories was created to form a graphical presentation of the sensory vocabulary. A selection of the oil samples was also evaluated by a trained sensory panel using descriptive analysis. Chemical analysis showed a positive correlation between primary and secondary oxidation products and sensory properties such as rancidity, chemical flavor and process flavor and a negative correlation between primary oxidation products and acidic. This research is a first step towards the broader objective of standardizing the sensory terminology related to marine oils. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modelling the spread of ragweed: Effects of habitat, climate change and diffusion

NASA Astrophysics Data System (ADS)

Vogl, G.; Smolik, M.; Stadler, L.-M.; Leitner, M.; Essl, F.; Dullinger, S.; Kleinbauer, I.; Peterseil, J.

2008-07-01

Ragweed (Ambrosia artemisiifolia L.) is an annual plant native in North America which has been invading Central Europe for 150 years. Caused by the warming of the European climate its spread process has accelerated in the last few decades. The pollen of ragweed evokes heavy allergies and what probably counts even more because of its bloom rather late in summer causes a second wave of allergy when other pollen allergies have decayed. We have reconstructed the invasion process of ragweed in Austria by collecting all records until the year 2005. Austria was subdivided into more than 2600 grid cells of ≈35 text{km}^2 each. Ragweed records were related to environmental descriptors (average temperatures, land use, etc.) by means of logistic regression models, and the suitability of grid cells as habitat for ragweed was determined. This enabled modelling of the diffusive spread of ragweed from 1990 to 2005. The results of the simulations were compared with the observed data, and thus the model was optimised. We then incorporated regional climate change models, in particular increased July mean temperatures of +2.3 ^circtext{C} in 2050, increasing considerably future habitat suitability. This is used for predicting the drastic dispersal of ragweed during the forthcoming decades.

Tree phylogenetic diversity promotes host-parasitoid interactions.

PubMed

Staab, Michael; Bruelheide, Helge; Durka, Walter; Michalski, Stefan; Purschke, Oliver; Zhu, Chao-Dong; Klein, Alexandra-Maria

2016-07-13

Evidence from grassland experiments suggests that a plant community's phylogenetic diversity (PD) is a strong predictor of ecosystem processes, even stronger than species richness per se This has, however, never been extended to species-rich forests and host-parasitoid interactions. We used cavity-nesting Hymenoptera and their parasitoids collected in a subtropical forest as a model system to test whether hosts, parasitoids, and their interactions are influenced by tree PD and a comprehensive set of environmental variables, including tree species richness. Parasitism rate and parasitoid abundance were positively correlated with tree PD. All variables describing parasitoids decreased with elevation, and were, except parasitism rate, dependent on host abundance. Quantitative descriptors of host-parasitoid networks were independent of the environment. Our study indicates that host-parasitoid interactions in species-rich forests are related to the PD of the tree community, which influences parasitism rates through parasitoid abundance. We show that effects of tree community PD are much stronger than effects of tree species richness, can cascade to high trophic levels, and promote trophic interactions. As during habitat modification phylogenetic information is usually lost non-randomly, even species-rich habitats may not be able to continuously provide the ecosystem process parasitism if the evolutionarily most distinct plant lineages vanish. © 2016 The Author(s).

Fugacity ratio estimations for high-melting rigid aromatic compounds.

PubMed

Van Noort, Paul C M

2004-07-01

Prediction of the environmental fate of organic compounds requires knowledge of their tendency to stay in the gas and water phase. Vapor pressure and aqueous solubility are commonly used descriptors for these processes. Depending on the type of distribution process, values for either the pure solid state or the (subcooled) liquid state have to be used. Values for the (subcooled) liquid state can be calculated from those for the solid state, and vice versa, using the fugacity ratio. Fugacity ratios are usually calculated from the entropy of fusion and the melting point. For polycyclic aromatic hydrocarbons, chlorobenzenes, chlorodibenzofuranes, and chlorodibenzo(p)dioxins, fugacity ratios calculated using experimental entropies of fusion were systematically less than those obtained from a thermodynamically more rigorous approach using heat capacity data. The deviation was more than 1 order of magnitude at the highest melting point. The use of a universal value for the entropy of fusion of 56 J/molK resulted in either over or underestimation by up to more than 1 order of magnitude. A simple correction factor, based on the melting point only, was derived. This correction factor allowed the fugacity ratios to be estimated from experimental entropies of fusion and melting point with an accuracy better than 0.1-0.2 log units. Copyright 2004 Elsevier Ltd.

Recent advances in the in silico modelling of UDP glucuronosyltransferase substrates.

PubMed

Sorich, Michael J; Smith, Paul A; Miners, John O; Mackenzie, Peter I; McKinnon, Ross A

2008-01-01

UDP glucurononosyltransferases (UGT) are a superfamily of enzymes that catalyse the conjugation of a range of structurally diverse drugs, environmental and endogenous chemicals with glucuronic acid. This process plays a significant role in the clearance and detoxification of many chemicals. Over the last decade the regulation and substrate profiles of UGT isoforms have been increasingly characterised. The resulting data has facilitated the prototyping of ligand based in silico models capable of predicting, and gaining insights into, binding affinity and the substrate- and regio- selectivity of glucuronidation by UGT isoforms. Pharmacophore modelling has produced particularly insightful models and quantitative structure-activity relationships based on machine learning algorithms result in accurate predictions. Simple structural chemical descriptors were found to capture much of the chemical information relevant to UGT metabolism. However, quantum chemical properties of molecules and the nucleophilic atoms in the molecule can enhance both the predictivity and chemical intuitiveness of structure-activity models. Chemical diversity analysis of known substrates has shown some bias towards chemicals with aromatic and aliphatic hydroxyl groups. Future progress in in silico development will depend on larger and more diverse high quality metabolic datasets. Furthermore, improved protein structure data on UGTs will enable the application of structural modelling techniques likely leading to greater insight into the binding and reactive processes of UGT catalysed glucuronidation.

Breast Imaging Reporting and Data System (BI-RADS) breast composition descriptors: Automated measurement development for full field digital mammography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fowler, E. E.; Sellers, T. A.; Lu, B.

Purpose: The Breast Imaging Reporting and Data System (BI-RADS) breast composition descriptors are used for standardized mammographic reporting and are assessed visually. This reporting is clinically relevant because breast composition can impact mammographic sensitivity and is a breast cancer risk factor. New techniques are presented and evaluated for generating automated BI-RADS breast composition descriptors using both raw and calibrated full field digital mammography (FFDM) image data.Methods: A matched case-control dataset with FFDM images was used to develop three automated measures for the BI-RADS breast composition descriptors. Histograms of each calibrated mammogram in the percent glandular (pg) representation were processed tomore » create the new BR{sub pg} measure. Two previously validated measures of breast density derived from calibrated and raw mammograms were converted to the new BR{sub vc} and BR{sub vr} measures, respectively. These three measures were compared with the radiologist-reported BI-RADS compositions assessments from the patient records. The authors used two optimization strategies with differential evolution to create these measures: method-1 used breast cancer status; and method-2 matched the reported BI-RADS descriptors. Weighted kappa (κ) analysis was used to assess the agreement between the new measures and the reported measures. Each measure's association with breast cancer was evaluated with odds ratios (ORs) adjusted for body mass index, breast area, and menopausal status. ORs were estimated as per unit increase with 95% confidence intervals.Results: The three BI-RADS measures generated by method-1 had κ between 0.25–0.34. These measures were significantly associated with breast cancer status in the adjusted models: (a) OR = 1.87 (1.34, 2.59) for BR{sub pg}; (b) OR = 1.93 (1.36, 2.74) for BR{sub vc}; and (c) OR = 1.37 (1.05, 1.80) for BR{sub vr}. The measures generated by method-2 had κ between 0.42–0.45. Two of these measures were significantly associated with breast cancer status in the adjusted models: (a) OR = 1.95 (1.24, 3.09) for BR{sub pg}; (b) OR = 1.42 (0.87, 2.32) for BR{sub vc}; and (c) OR = 2.13 (1.22, 3.72) for BR{sub vr}. The radiologist-reported measures from the patient records showed a similar association, OR = 1.49 (0.99, 2.24), although only borderline statistically significant.Conclusions: A general framework was developed and validated for converting calibrated mammograms and continuous measures of breast density to fully automated approximations for the BI-RADS breast composition descriptors. The techniques are general and suitable for a broad range of clinical and research applications.« less

An object-based approach for areal rainfall estimation and validation of atmospheric models

NASA Astrophysics Data System (ADS)

Troemel, Silke; Simmer, Clemens

2010-05-01

An object-based approach for areal rainfall estimation is applied to pseudo-radar data simulated of a weatherforecast model as well as to real radar volume data. The method aims at an as fully as possible exploitation of three-dimensional radar signals produced by precipitation generating systems during their lifetime to enhance areal rainfall estimation. Therefore tracking of radar-detected precipitation-centroids is performed and rain events are investigated using so-called Integral Radar Volume Descriptors (IRVD) containing relevant information of the underlying precipitation process. Some investigated descriptors are statistical quantities from the radar reflectivities within the boundary of a tracked rain cell like the area mean reflectivity or the compactness of a cell; others evaluate the mean vertical structure during the tracking period at the near surface reflectivity-weighted center of the cell like the mean effective efficiency or the mean echo top height. The stage of evolution of a system is given by the trend in the brightband fraction or related quantities. Furthermore, two descriptors not directly derived from radar data are considered: the mean wind shear and an orographic rainfall amplifier. While in case of pseudo-radar data a model based on a small set of IRVDs alone provides rainfall estimates of high accuracy, the application of such a model to the real world remains within the accuracies achievable with a constant Z-R-relationship. However, a combined model based on single IRVDs and the Marshall-Palmer Z-R-estimator already provides considerable enhancements even though the resolution of the data base used has room for improvement. The mean echo top height, the mean effective efficiency, the empirical standard deviation and the Marshall-Palmer estimator are detected for the final rainfall estimator. High correlations between storm height and rain rates, a shift of the probability distribution to higher values with increasing effective efficiency, and the possibility to classify continental and maritime systems using the effective efficiency confirm the informative value of the qualified descriptors. The IRVDs especially correct for the underestimation in case of intense rain events, and the information content of descriptors is most likely higher than demonstrated so far. We used quite sparse information about meteorological variables needed for the calculation of some IRVDs from single radiosoundings, and several descriptors suffered from the range-dependent vertical resolution of the reflectivity profile. Inclusion of neighbouring radars and assimilation runs of weather forecasting models will further enhance the accuracy of rainfall estimates. Finally, the clear difference between the IRVD selection from the pseudo-radar data and from the real world data hint to a new object-based avenue for the validation of higher resolution atmospheric models and for evaluating their potential to digest radar observations in data assimilation schemes.

The recursive combination filter approach of pre-processing for the estimation of standard deviation of RR series.

PubMed

Mishra, Alok; Swati, D

2015-09-01

Variation in the interval between the R-R peaks of the electrocardiogram represents the modulation of the cardiac oscillations by the autonomic nervous system. This variation is contaminated by anomalous signals called ectopic beats, artefacts or noise which mask the true behaviour of heart rate variability. In this paper, we have proposed a combination filter of recursive impulse rejection filter and recursive 20% filter, with recursive application and preference of replacement over removal of abnormal beats to improve the pre-processing of the inter-beat intervals. We have tested this novel recursive combinational method with median method replacement to estimate the standard deviation of normal to normal (SDNN) beat intervals of congestive heart failure (CHF) and normal sinus rhythm subjects. This work discusses the improvement in pre-processing over single use of impulse rejection filter and removal of abnormal beats for heart rate variability for the estimation of SDNN and Poncaré plot descriptors (SD1, SD2, and SD1/SD2) in detail. We have found the 22 ms value of SDNN and 36 ms value of SD2 descriptor of Poincaré plot as clinical indicators in discriminating the normal cases from CHF cases. The pre-processing is also useful in calculation of Lyapunov exponent which is a nonlinear index as Lyapunov exponents calculated after proposed pre-processing modified in a way that it start following the notion of less complex behaviour of diseased states.

Music Identification System Using MPEG-7 Audio Signature Descriptors

PubMed Central

You, Shingchern D.; Chen, Wei-Hwa; Chen, Woei-Kae

2013-01-01

This paper describes a multiresolution system based on MPEG-7 audio signature descriptors for music identification. Such an identification system may be used to detect illegally copied music circulated over the Internet. In the proposed system, low-resolution descriptors are used to search likely candidates, and then full-resolution descriptors are used to identify the unknown (query) audio. With this arrangement, the proposed system achieves both high speed and high accuracy. To deal with the problem that a piece of query audio may not be inside the system's database, we suggest two different methods to find the decision threshold. Simulation results show that the proposed method II can achieve an accuracy of 99.4% for query inputs both inside and outside the database. Overall, it is highly possible to use the proposed system for copyright control. PMID:23533359

Multiple node remote messaging

DOEpatents

Blumrich, Matthias A.; Chen, Dong; Gara, Alan G.; Giampapa, Mark E.; Heidelberger, Philip; Ohmacht, Martin; Salapura, Valentina; Steinmacher-Burow, Burkhard; Vranas, Pavlos

2010-08-31

A method for passing remote messages in a parallel computer system formed as a network of interconnected compute nodes includes that a first compute node (A) sends a single remote message to a remote second compute node (B) in order to control the remote second compute node (B) to send at least one remote message. The method includes various steps including controlling a DMA engine at first compute node (A) to prepare the single remote message to include a first message descriptor and at least one remote message descriptor for controlling the remote second compute node (B) to send at least one remote message, including putting the first message descriptor into an injection FIFO at the first compute node (A) and sending the single remote message and the at least one remote message descriptor to the second compute node (B).

Applications of genetic algorithms on the structure-activity relationship analysis of some cinnamamides.

PubMed

Hou, T J; Wang, J M; Liao, N; Xu, X J

1999-01-01

Quantitative structure-activity relationships (QSARs) for 35 cinnamamides were studied. By using a genetic algorithm (GA), a group of multiple regression models with high fitness scores was generated. From the statistical analyses of the descriptors used in the evolution procedure, the principal features affecting the anticonvulsant activity were found. The significant descriptors include the partition coefficient, the molar refraction, the Hammet sigma constant of the substituents on the benzene ring, and the formation energy of the molecules. It could be found that the steric complementarity and the hydrophobic interaction between the inhibitors and the receptor were very important to the biological activity, while the contribution of the electronic effect was not so obvious. Moreover, by construction of the spline models for these four principal descriptors, the effective range for each descriptor was identified.

Conceptual DFT Descriptors of Amino Acids with Potential Corrosion Inhibition Properties Calculated with the Latest Minnesota Density Functionals.

PubMed

Frau, Juan; Glossman-Mitnik, Daniel

2017-01-01

Amino acids and peptides have the potential to perform as corrosion inhibitors. The chemical reactivity descriptors that arise from Conceptual DFT for the twenty natural amino acids have been calculated by using the latest Minnesota family of density functionals. In order to verify the validity of the calculation of the descriptors directly from the HOMO and LUMO, a comparison has been performed with those obtained through ΔSCF results. Moreover, the active sites for nucleophilic and electrophilic attacks have been identified through Fukui function indices, the dual descriptor Δf( r ) and the electrophilic and nucleophilic Parr functions. The results could be of interest as a starting point for the study of large peptides where the calculation of the radical cation and anion of each system may be computationally harder and costly.

Chemical reactivity indices for the complete series of chlorinated benzenes: solvent effect.

PubMed

Padmanabhan, J; Parthasarathi, R; Subramanian, V; Chattaraj, P K

2006-03-02

We present a comprehensive analysis to probe the effect of solvation on the reactivity of the complete series of chlorobenzenes through the conceptual density functional theory (DFT)-based global and local descriptors. We propose a multiphilic descriptor in this study to explore the nature of attack at a particular site in a molecule. It is defined as the difference between nucleophilic and electrophilic condensed philicity functions. This descriptor is capable of explaining both the nucleophilicity and electrophilicity of the given atomic sites in the molecule simultaneously. The predictive ability of this descriptor is tested on the complete series of chlorobenzenes in gas and solvent media. A structure-toxicity analysis of these entire sets of chlorobenzenes toward aquatic organisms demonstrates the importance of the electrophilicity index in the prediction of the reactivity/toxicity.

Learning Optimized Local Difference Binaries for Scalable Augmented Reality on Mobile Devices.

PubMed

Xin Yang; Kwang-Ting Cheng

2014-06-01

The efficiency, robustness and distinctiveness of a feature descriptor are critical to the user experience and scalability of a mobile augmented reality (AR) system. However, existing descriptors are either too computationally expensive to achieve real-time performance on a mobile device such as a smartphone or tablet, or not sufficiently robust and distinctive to identify correct matches from a large database. As a result, current mobile AR systems still only have limited capabilities, which greatly restrict their deployment in practice. In this paper, we propose a highly efficient, robust and distinctive binary descriptor, called Learning-based Local Difference Binary (LLDB). LLDB directly computes a binary string for an image patch using simple intensity and gradient difference tests on pairwise grid cells within the patch. To select an optimized set of grid cell pairs, we densely sample grid cells from an image patch and then leverage a modified AdaBoost algorithm to automatically extract a small set of critical ones with the goal of maximizing the Hamming distance between mismatches while minimizing it between matches. Experimental results demonstrate that LLDB is extremely fast to compute and to match against a large database due to its high robustness and distinctiveness. Compared to the state-of-the-art binary descriptors, primarily designed for speed, LLDB has similar efficiency for descriptor construction, while achieving a greater accuracy and faster matching speed when matching over a large database with 2.3M descriptors on mobile devices.

Improved nucleic acid descriptors for siRNA efficacy prediction.

PubMed

Sciabola, Simone; Cao, Qing; Orozco, Modesto; Faustino, Ignacio; Stanton, Robert V

2013-02-01

Although considerable progress has been made recently in understanding how gene silencing is mediated by the RNAi pathway, the rational design of effective sequences is still a challenging task. In this article, we demonstrate that including three-dimensional descriptors improved the discrimination between active and inactive small interfering RNAs (siRNAs) in a statistical model. Five descriptor types were used: (i) nucleotide position along the siRNA sequence, (ii) nucleotide composition in terms of presence/absence of specific combinations of di- and trinucleotides, (iii) nucleotide interactions by means of a modified auto- and cross-covariance function, (iv) nucleotide thermodynamic stability derived by the nearest neighbor model representation and (v) nucleic acid structure flexibility. The duplex flexibility descriptors are derived from extended molecular dynamics simulations, which are able to describe the sequence-dependent elastic properties of RNA duplexes, even for non-standard oligonucleotides. The matrix of descriptors was analysed using three statistical packages in R (partial least squares, random forest, and support vector machine), and the most predictive model was implemented in a modeling tool we have made publicly available through SourceForge. Our implementation of new RNA descriptors coupled with appropriate statistical algorithms resulted in improved model performance for the selection of siRNA candidates when compared with publicly available siRNA prediction tools and previously published test sets. Additional validation studies based on in-house RNA interference projects confirmed the robustness of the scoring procedure in prospective studies.

Development of bovine serum albumin-water partition coefficients predictive models for ionogenic organic chemicals based on chemical form adjusted descriptors.

PubMed

Ding, Feng; Yang, Xianhai; Chen, Guosong; Liu, Jining; Shi, Lili; Chen, Jingwen

2017-10-01

The partition coefficients between bovine serum albumin (BSA) and water (K BSA/w ) for ionogenic organic chemicals (IOCs) were different greatly from those of neutral organic chemicals (NOCs). For NOCs, several excellent models were developed to predict their logK BSA/w . However, it was found that the conventional descriptors are inappropriate for modeling logK BSA/w of IOCs. Thus, alternative approaches are urgently needed to develop predictive models for K BSA/w of IOCs. In this study, molecular descriptors that can be used to characterize the ionization effects (e.g. chemical form adjusted descriptors) were calculated and used to develop predictive models for logK BSA/w of IOCs. The models developed had high goodness-of-fit, robustness, and predictive ability. The predictor variables selected to construct the models included the chemical form adjusted averages of the negative potentials on the molecular surface (V s-adj - ), the chemical form adjusted molecular dipole moment (dipolemoment adj ), the logarithm of the n-octanol/water distribution coefficient (logD). As these molecular descriptors can be calculated from their molecular structures directly, the developed model can be easily used to fill the logK BSA/w data gap for other IOCs within the applicability domain. Furthermore, the chemical form adjusted descriptors calculated in this study also could be used to construct predictive models on other endpoints of IOCs. Copyright © 2017 Elsevier Inc. All rights reserved.

Molecular descriptor subset selection in theoretical peptide quantitative structure-retention relationship model development using nature-inspired optimization algorithms.

PubMed

Žuvela, Petar; Liu, J Jay; Macur, Katarzyna; Bączek, Tomasz

2015-10-06

In this work, performance of five nature-inspired optimization algorithms, genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), firefly algorithm (FA), and flower pollination algorithm (FPA), was compared in molecular descriptor selection for development of quantitative structure-retention relationship (QSRR) models for 83 peptides that originate from eight model proteins. The matrix with 423 descriptors was used as input, and QSRR models based on selected descriptors were built using partial least squares (PLS), whereas root mean square error of prediction (RMSEP) was used as a fitness function for their selection. Three performance criteria, prediction accuracy, computational cost, and the number of selected descriptors, were used to evaluate the developed QSRR models. The results show that all five variable selection methods outperform interval PLS (iPLS), sparse PLS (sPLS), and the full PLS model, whereas GA is superior because of its lowest computational cost and higher accuracy (RMSEP of 5.534%) with a smaller number of variables (nine descriptors). The GA-QSRR model was validated initially through Y-randomization. In addition, it was successfully validated with an external testing set out of 102 peptides originating from Bacillus subtilis proteomes (RMSEP of 22.030%). Its applicability domain was defined, from which it was evident that the developed GA-QSRR exhibited strong robustness. All the sources of the model's error were identified, thus allowing for further application of the developed methodology in proteomics.

Grading system to categorize breast MRI using BI-RADS 5th edition: a statistical study of non-mass enhancement descriptors in terms of probability of malignancy.

PubMed

Asada, Tatsunori; Yamada, Takayuki; Kanemaki, Yoshihide; Fujiwara, Keishi; Okamoto, Satoko; Nakajima, Yasuo

2018-03-01

To analyze the association of breast non-mass enhancement descriptors in the BI-RADS 5th edition with malignancy, and to establish a grading system and categorization of descriptors. This study was approved by our institutional review board. A total of 213 patients were enrolled. Breast MRI was performed with a 1.5-T MRI scanner using a 16-channel breast radiofrequency coil. Two radiologists determined internal enhancement and distribution of non-mass enhancement by consensus. Corresponding pathologic diagnoses were obtained by either biopsy or surgery. The probability of malignancy by descriptor was analyzed using Fisher's exact test and multivariate logistic regression analysis. The probability of malignancy by category was analyzed using Fisher's exact and multi-group comparison tests. One hundred seventy-eight lesions were malignant. Multivariate model analysis showed that internal enhancement (homogeneous vs others, p < 0.001, heterogeneous and clumped vs clustered ring, p = 0.003) and distribution (focal and linear vs segmental, p < 0.001) were the significant explanatory variables. The descriptors were classified into three grades of suspicion, and the categorization (3, 4A, 4B, 4C, and 5) by sum-up grades showed an incremental increase in the probability of malignancy (p < 0.0001). The three-grade criteria and categorization by sum-up grades of descriptors appear valid for non-mass enhancement.

Three-Dimensional Object Recognition and Registration for Robotic Grasping Systems Using a Modified Viewpoint Feature Histogram

PubMed Central

Chen, Chin-Sheng; Chen, Po-Chun; Hsu, Chih-Ming

2016-01-01

This paper presents a novel 3D feature descriptor for object recognition and to identify poses when there are six-degrees-of-freedom for mobile manipulation and grasping applications. Firstly, a Microsoft Kinect sensor is used to capture 3D point cloud data. A viewpoint feature histogram (VFH) descriptor for the 3D point cloud data then encodes the geometry and viewpoint, so an object can be simultaneously recognized and registered in a stable pose and the information is stored in a database. The VFH is robust to a large degree of surface noise and missing depth information so it is reliable for stereo data. However, the pose estimation for an object fails when the object is placed symmetrically to the viewpoint. To overcome this problem, this study proposes a modified viewpoint feature histogram (MVFH) descriptor that consists of two parts: a surface shape component that comprises an extended fast point feature histogram and an extended viewpoint direction component. The MVFH descriptor characterizes an object’s pose and enhances the system’s ability to identify objects with mirrored poses. Finally, the refined pose is further estimated using an iterative closest point when the object has been recognized and the pose roughly estimated by the MVFH descriptor and it has been registered on a database. The estimation results demonstrate that the MVFH feature descriptor allows more accurate pose estimation. The experiments also show that the proposed method can be applied in vision-guided robotic grasping systems. PMID:27886080

A short feature vector for image matching: The Log-Polar Magnitude feature descriptor

PubMed Central

Hast, Anders; Wählby, Carolina; Sintorn, Ida-Maria

2017-01-01

The choice of an optimal feature detector-descriptor combination for image matching often depends on the application and the image type. In this paper, we propose the Log-Polar Magnitude feature descriptor—a rotation, scale, and illumination invariant descriptor that achieves comparable performance to SIFT on a large variety of image registration problems but with much shorter feature vectors. The descriptor is based on the Log-Polar Transform followed by a Fourier Transform and selection of the magnitude spectrum components. Selecting different frequency components allows optimizing for image patterns specific for a particular application. In addition, by relying only on coordinates of the found features and (optionally) feature sizes our descriptor is completely detector independent. We propose 48- or 56-long feature vectors that potentially can be shortened even further depending on the application. Shorter feature vectors result in better memory usage and faster matching. This combined with the fact that the descriptor does not require a time-consuming feature orientation estimation (the rotation invariance is achieved solely by using the magnitude spectrum of the Log-Polar Transform) makes it particularly attractive to applications with limited hardware capacity. Evaluation is performed on the standard Oxford dataset and two different microscopy datasets; one with fluorescence and one with transmission electron microscopy images. Our method performs better than SURF and comparable to SIFT on the Oxford dataset, and better than SIFT on both microscopy datasets indicating that it is particularly useful in applications with microscopy images. PMID:29190737

An image retrieval framework for real-time endoscopic image retargeting.

PubMed

Ye, Menglong; Johns, Edward; Walter, Benjamin; Meining, Alexander; Yang, Guang-Zhong

2017-08-01

Serial endoscopic examinations of a patient are important for early diagnosis of malignancies in the gastrointestinal tract. However, retargeting for optical biopsy is challenging due to extensive tissue variations between examinations, requiring the method to be tolerant to these changes whilst enabling real-time retargeting. This work presents an image retrieval framework for inter-examination retargeting. We propose both a novel image descriptor tolerant of long-term tissue changes and a novel descriptor matching method in real time. The descriptor is based on histograms generated from regional intensity comparisons over multiple scales, offering stability over long-term appearance changes at the higher levels, whilst remaining discriminative at the lower levels. The matching method then learns a hashing function using random forests, to compress the string and allow for fast image comparison by a simple Hamming distance metric. A dataset that contains 13 in vivo gastrointestinal videos was collected from six patients, representing serial examinations of each patient, which includes videos captured with significant time intervals. Precision-recall for retargeting shows that our new descriptor outperforms a number of alternative descriptors, whilst our hashing method outperforms a number of alternative hashing approaches. We have proposed a novel framework for optical biopsy in serial endoscopic examinations. A new descriptor, combined with a novel hashing method, achieves state-of-the-art retargeting, with validation on in vivo videos from six patients. Real-time performance also allows for practical integration without disturbing the existing clinical workflow.

Texture Descriptors Ensembles Enable Image-Based Classification of Maturation of Human Stem Cell-Derived Retinal Pigmented Epithelium

PubMed Central

Caetano dos Santos, Florentino Luciano; Skottman, Heli; Juuti-Uusitalo, Kati; Hyttinen, Jari

2016-01-01

Aims A fast, non-invasive and observer-independent method to analyze the homogeneity and maturity of human pluripotent stem cell (hPSC) derived retinal pigment epithelial (RPE) cells is warranted to assess the suitability of hPSC-RPE cells for implantation or in vitro use. The aim of this work was to develop and validate methods to create ensembles of state-of-the-art texture descriptors and to provide a robust classification tool to separate three different maturation stages of RPE cells by using phase contrast microscopy images. The same methods were also validated on a wide variety of biological image classification problems, such as histological or virus image classification. Methods For image classification we used different texture descriptors, descriptor ensembles and preprocessing techniques. Also, three new methods were tested. The first approach was an ensemble of preprocessing methods, to create an additional set of images. The second was the region-based approach, where saliency detection and wavelet decomposition divide each image in two different regions, from which features were extracted through different descriptors. The third method was an ensemble of Binarized Statistical Image Features, based on different sizes and thresholds. A Support Vector Machine (SVM) was trained for each descriptor histogram and the set of SVMs combined by sum rule. The accuracy of the computer vision tool was verified in classifying the hPSC-RPE cell maturation level. Dataset and Results The RPE dataset contains 1862 subwindows from 195 phase contrast images. The final descriptor ensemble outperformed the most recent stand-alone texture descriptors, obtaining, for the RPE dataset, an area under ROC curve (AUC) of 86.49% with the 10-fold cross validation and 91.98% with the leave-one-image-out protocol. The generality of the three proposed approaches was ascertained with 10 more biological image datasets, obtaining an average AUC greater than 97%. Conclusions Here we showed that the developed ensembles of texture descriptors are able to classify the RPE cell maturation stage. Moreover, we proved that preprocessing and region-based decomposition improves many descriptors’ accuracy in biological dataset classification. Finally, we built the first public dataset of stem cell-derived RPE cells, which is publicly available to the scientific community for classification studies. The proposed tool is available at https://www.dei.unipd.it/node/2357 and the RPE dataset at http://www.biomeditech.fi/data/RPE_dataset/. Both are available at https://figshare.com/s/d6fb591f1beb4f8efa6f. PMID:26895509

Quantitative analysis of adsorptive interactions of ionic and neutral pharmaceuticals and other chemicals with the surface of Escherichia coli cells in aquatic environment.

PubMed

Cho, Chul-Woong; Park, Jeong-Soo; Zhao, Yufeng; Yun, Yeoung-Sang

2017-08-01

Since Escherichia coli is ubiquitous in nature and has been applied to biological, chemical, and environmental processes, molecular-level understanding of adsorptive interactions between chemicals and the bacterial surface is of great importance. To characterise the adsorption properties of the surface of E. coli cells in aquatic environment, the binding affinities (log K d ) of calibration compounds were experimentally measured, and then based on the values and numerically well-defined molecular interaction forces, i.e. linear free energy relationship (LFER) descriptors, a predictive model was developed. The examined substances are composed of cations, anions, and neutral compounds, and the used LFER descriptors are excess molar refraction (E), dipolarity/polarisability (S), H-bonding acidity (A) and basicity (B), McGowan volume (V), and coulombic interactions of cations (J + ) and anions (J - ). In experimental results, adsorption of anions on the bacterial surface was not observed, while cations exhibited high affinities. In case of neutral compounds, their low quantities were adsorbed, however whose affinities were mostly lower than those of cations. In a LFER study, it was shown that cationic interaction term has the best correlation in R 2 of 0.691 and sequential additions of S, A, and V help to increase the prediction accuracy. The LFER model (log K d  = - 0.72-0.79 S + 0.81 A + 0.41 V + 0.85 J + ) could predict the log K d in R 2 of 0.871 and SE of 0.402 log unit, and then to check robustness and predictability of the model, we internally validated it by a leave-one-out cross validation (Q 2 LOO ) study. As a result, the Q 2 LOO value was estimated to be 0.826, which was larger than standard of model acceptability (>0.5). Copyright © 2017 Elsevier Ltd. All rights reserved.

In silico prediction of toxicity of phenols to Tetrahymena pyriformis by using genetic algorithm and decision tree-based modeling approach.

PubMed

Abbasitabar, Fatemeh; Zare-Shahabadi, Vahid

2017-04-01

Risk assessment of chemicals is an important issue in environmental protection; however, there is a huge lack of experimental data for a large number of end-points. The experimental determination of toxicity of chemicals involves high costs and time-consuming process. In silico tools such as quantitative structure-toxicity relationship (QSTR) models, which are constructed on the basis of computational molecular descriptors, can predict missing data for toxic end-points for existing or even not yet synthesized chemicals. Phenol derivatives are known to be aquatic pollutants. With this background, we aimed to develop an accurate and reliable QSTR model for the prediction of toxicity of 206 phenols to Tetrahymena pyriformis. A multiple linear regression (MLR)-based QSTR was obtained using a powerful descriptor selection tool named Memorized_ACO algorithm. Statistical parameters of the model were 0.72 and 0.68 for R training 2 and R test 2 , respectively. To develop a high-quality QSTR model, classification and regression tree (CART) was employed. Two approaches were considered: (1) phenols were classified into different modes of action using CART and (2) the phenols in the training set were partitioned to several subsets by a tree in such a manner that in each subset, a high-quality MLR could be developed. For the first approach, the statistical parameters of the resultant QSTR model were improved to 0.83 and 0.75 for R training 2 and R test 2 , respectively. Genetic algorithm was employed in the second approach to obtain an optimal tree, and it was shown that the final QSTR model provided excellent prediction accuracy for the training and test sets (R training 2 and R test 2 were 0.91 and 0.93, respectively). The mean absolute error for the test set was computed as 0.1615. Copyright © 2016 Elsevier Ltd. All rights reserved.

Principal component analysis on molecular descriptors as an alternative point of view in the search of new Hsp90 inhibitors.

PubMed

Lauria, Antonino; Ippolito, Mario; Almerico, Anna Maria

2009-10-01

Inhibiting a protein that regulates multiple signal transduction pathways in cancer cells is an attractive goal for cancer therapy. Heat shock protein 90 (Hsp90) is one of the most promising molecular targets for such an approach. In fact, Hsp90 is a ubiquitous molecular chaperone protein that is involved in folding, activating and assembling of many key mediators of signal transduction, cellular growth, differentiation, stress-response and apoptothic pathways. With the aim to analyze which molecular descriptors have the higher importance in the binding interactions of these classes, we first performed molecular docking experiments on the 187 Hsp90 inhibitors included in the BindingDB, a public database of measured binding affinities. Further, for each frozen conformation obtained from the docking, a set of 250 molecular descriptors was calculated, and the resulting Structure/Descriptors matrix was submitted to Principal Component Analysis. From the factor scores it emerged a good clusterization among similar compounds both in terms of structural class and activity spectrum, while examination of the loadings of the first two factors also allowed to study the classes of descriptors which mainly contribute to each one.

Object Tracking Using Adaptive Covariance Descriptor and Clustering-Based Model Updating for Visual Surveillance

PubMed Central

Qin, Lei; Snoussi, Hichem; Abdallah, Fahed

2014-01-01

We propose a novel approach for tracking an arbitrary object in video sequences for visual surveillance. The first contribution of this work is an automatic feature extraction method that is able to extract compact discriminative features from a feature pool before computing the region covariance descriptor. As the feature extraction method is adaptive to a specific object of interest, we refer to the region covariance descriptor computed using the extracted features as the adaptive covariance descriptor. The second contribution is to propose a weakly supervised method for updating the object appearance model during tracking. The method performs a mean-shift clustering procedure among the tracking result samples accumulated during a period of time and selects a group of reliable samples for updating the object appearance model. As such, the object appearance model is kept up-to-date and is prevented from contamination even in case of tracking mistakes. We conducted comparing experiments on real-world video sequences, which confirmed the effectiveness of the proposed approaches. The tracking system that integrates the adaptive covariance descriptor and the clustering-based model updating method accomplished stable object tracking on challenging video sequences. PMID:24865883

MBR-SIFT: A mirror reflected invariant feature descriptor using a binary representation for image matching.

PubMed

Su, Mingzhe; Ma, Yan; Zhang, Xiangfen; Wang, Yan; Zhang, Yuping

2017-01-01

The traditional scale invariant feature transform (SIFT) method can extract distinctive features for image matching. However, it is extremely time-consuming in SIFT matching because of the use of the Euclidean distance measure. Recently, many binary SIFT (BSIFT) methods have been developed to improve matching efficiency; however, none of them is invariant to mirror reflection. To address these problems, in this paper, we present a horizontal or vertical mirror reflection invariant binary descriptor named MBR-SIFT, in addition to a novel image matching approach. First, 16 cells in the local region around the SIFT keypoint are reorganized, and then the 128-dimensional vector of the SIFT descriptor is transformed into a reconstructed vector according to eight directions. Finally, the MBR-SIFT descriptor is obtained after binarization and reverse coding. To improve the matching speed and accuracy, a fast matching algorithm that includes a coarse-to-fine two-step matching strategy in addition to two similarity measures for the MBR-SIFT descriptor are proposed. Experimental results on the UKBench dataset show that the proposed method not only solves the problem of mirror reflection, but also ensures desirable matching accuracy and speed.

MBR-SIFT: A mirror reflected invariant feature descriptor using a binary representation for image matching

PubMed Central

Su, Mingzhe; Ma, Yan; Zhang, Xiangfen; Wang, Yan; Zhang, Yuping

2017-01-01

The traditional scale invariant feature transform (SIFT) method can extract distinctive features for image matching. However, it is extremely time-consuming in SIFT matching because of the use of the Euclidean distance measure. Recently, many binary SIFT (BSIFT) methods have been developed to improve matching efficiency; however, none of them is invariant to mirror reflection. To address these problems, in this paper, we present a horizontal or vertical mirror reflection invariant binary descriptor named MBR-SIFT, in addition to a novel image matching approach. First, 16 cells in the local region around the SIFT keypoint are reorganized, and then the 128-dimensional vector of the SIFT descriptor is transformed into a reconstructed vector according to eight directions. Finally, the MBR-SIFT descriptor is obtained after binarization and reverse coding. To improve the matching speed and accuracy, a fast matching algorithm that includes a coarse-to-fine two-step matching strategy in addition to two similarity measures for the MBR-SIFT descriptor are proposed. Experimental results on the UKBench dataset show that the proposed method not only solves the problem of mirror reflection, but also ensures desirable matching accuracy and speed. PMID:28542537

The implementation of aerial object recognition algorithm based on contour descriptor in FPGA-based on-board vision system

NASA Astrophysics Data System (ADS)

Babayan, Pavel; Smirnov, Sergey; Strotov, Valery

2017-10-01

This paper describes the aerial object recognition algorithm for on-board and stationary vision system. Suggested algorithm is intended to recognize the objects of a specific kind using the set of the reference objects defined by 3D models. The proposed algorithm based on the outer contour descriptor building. The algorithm consists of two stages: learning and recognition. Learning stage is devoted to the exploring of reference objects. Using 3D models we can build the database containing training images by rendering the 3D model from viewpoints evenly distributed on a sphere. Sphere points distribution is made by the geosphere principle. Gathered training image set is used for calculating descriptors, which will be used in the recognition stage of the algorithm. The recognition stage is focusing on estimating the similarity of the captured object and the reference objects by matching an observed image descriptor and the reference object descriptors. The experimental research was performed using a set of the models of the aircraft of the different types (airplanes, helicopters, UAVs). The proposed orientation estimation algorithm showed good accuracy in all case studies. The real-time performance of the algorithm in FPGA-based vision system was demonstrated.

Chemical Sensor Array Response Modeling Using Quantitative Structure-Activity Relationships Technique

NASA Astrophysics Data System (ADS)

Shevade, Abhijit V.; Ryan, Margaret A.; Homer, Margie L.; Zhou, Hanying; Manfreda, Allison M.; Lara, Liana M.; Yen, Shiao-Pin S.; Jewell, April D.; Manatt, Kenneth S.; Kisor, Adam K.

We have developed a Quantitative Structure-Activity Relationships (QSAR) based approach to correlate the response of chemical sensors in an array with molecular descriptors. A novel molecular descriptor set has been developed; this set combines descriptors of sensing film-analyte interactions, representing sensor response, with a basic analyte descriptor set commonly used in QSAR studies. The descriptors are obtained using a combination of molecular modeling tools and empirical and semi-empirical Quantitative Structure-Property Relationships (QSPR) methods. The sensors under investigation are polymer-carbon sensing films which have been exposed to analyte vapors at parts-per-million (ppm) concentrations; response is measured as change in film resistance. Statistically validated QSAR models have been developed using Genetic Function Approximations (GFA) for a sensor array for a given training data set. The applicability of the sensor response models has been tested by using it to predict the sensor activities for test analytes not considered in the training set for the model development. The validated QSAR sensor response models show good predictive ability. The QSAR approach is a promising computational tool for sensing materials evaluation and selection. It can also be used to predict response of an existing sensing film to new target analytes.

Salient aspects of PBP2A-inhibition; A QSAR Study.

PubMed

Ogunleye, Adewale J; Eniafe, Gabriel O; Inyang, Olumide K; Adewumi, Benjamin; Omotuyi, Olaposi I

2018-05-15

Backgound: Inhibition of penicillin binding protein 2A (PBP2A) represents a sound drug design strategy in combatting Methicillin resistant Staphylococcus aureus (MRSA). Considering the urgent need for effective antimicrobials in combatting MRSA infections, we have developed a statistically robust ensemble of molecular descriptors (1, 2, & 3-D) from compounds targeting PBP2A in vivo. 37 (training set: 26, test set: 11) PBP2A-inhibitors were submitted for descriptor generation after which an unsupervised, non-exhaustive genetic algorithm (GA) was deployed for fishing out the best descriptor subset. Assignment of descriptors to a regression model was accomplished with the Partial Least Square (PLS) algorithm. At the end, an ensemble of 30 descriptors accurately predicted the ligand bioactivity, IC50 (R = 0.9996, R2 = 0.9992, R2a = 0.9949, SEE =, 0.2297 Q2LOO = 0.9741). Inferentially, we noticed that the overall efficacy of this model greatly depends on atomic polarizability and negative charge (electron) density. Besides the formula derived, the high dimensional model also offers critical insights into salient cheminformatics parameter to note during hit-to-lead PBP2A-antagonist optimization. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Automatic summarization of soccer highlights using audio-visual descriptors.

PubMed

Raventós, A; Quijada, R; Torres, Luis; Tarrés, Francesc

2015-01-01

Automatic summarization generation of sports video content has been object of great interest for many years. Although semantic descriptions techniques have been proposed, many of the approaches still rely on low-level video descriptors that render quite limited results due to the complexity of the problem and to the low capability of the descriptors to represent semantic content. In this paper, a new approach for automatic highlights summarization generation of soccer videos using audio-visual descriptors is presented. The approach is based on the segmentation of the video sequence into shots that will be further analyzed to determine its relevance and interest. Of special interest in the approach is the use of the audio information that provides additional robustness to the overall performance of the summarization system. For every video shot a set of low and mid level audio-visual descriptors are computed and lately adequately combined in order to obtain different relevance measures based on empirical knowledge rules. The final summary is generated by selecting those shots with highest interest according to the specifications of the user and the results of relevance measures. A variety of results are presented with real soccer video sequences that prove the validity of the approach.

Quantitative structure-property relationship analysis for the retention index of fragrance-like compounds on a polar stationary phase.

PubMed

Rojas, Cristian; Duchowicz, Pablo R; Tripaldi, Piercosimo; Pis Diez, Reinaldo

2015-11-27

A quantitative structure-property relationship (QSPR) was developed for modeling the retention index of 1184 flavor and fragrance compounds measured using a Carbowax 20M glass capillary gas chromatography column. The 4885 molecular descriptors were calculated using Dragon software, and then were simultaneously analyzed through multivariable linear regression analysis using the replacement method (RM) variable subset selection technique. We proceeded in three steps, the first one by considering all descriptor blocks, the second one by excluding conformational descriptor blocks, and the last one by analyzing only 3D-descriptor families. The models were validated through an external test set of compounds. Cross-validation methods such as leave-one-out and leave-many-out were applied, together with Y-randomization and applicability domain analysis. The developed model was used to estimate the I of a set of 22 molecules. The results clearly suggest that 3D-descriptors do not offer relevant information for modeling the retention index, while a topological index such as the Randić-like index from reciprocal squared distance matrix has a high relevance for this purpose. Copyright © 2015 Elsevier B.V. All rights reserved.

Magnostics: Image-Based Search of Interesting Matrix Views for Guided Network Exploration.

PubMed

Behrisch, Michael; Bach, Benjamin; Hund, Michael; Delz, Michael; Von Ruden, Laura; Fekete, Jean-Daniel; Schreck, Tobias

2017-01-01

In this work we address the problem of retrieving potentially interesting matrix views to support the exploration of networks. We introduce Matrix Diagnostics (or Magnostics), following in spirit related approaches for rating and ranking other visualization techniques, such as Scagnostics for scatter plots. Our approach ranks matrix views according to the appearance of specific visual patterns, such as blocks and lines, indicating the existence of topological motifs in the data, such as clusters, bi-graphs, or central nodes. Magnostics can be used to analyze, query, or search for visually similar matrices in large collections, or to assess the quality of matrix reordering algorithms. While many feature descriptors for image analyzes exist, there is no evidence how they perform for detecting patterns in matrices. In order to make an informed choice of feature descriptors for matrix diagnostics, we evaluate 30 feature descriptors-27 existing ones and three new descriptors that we designed specifically for MAGNOSTICS-with respect to four criteria: pattern response, pattern variability, pattern sensibility, and pattern discrimination. We conclude with an informed set of six descriptors as most appropriate for Magnostics and demonstrate their application in two scenarios; exploring a large collection of matrices and analyzing temporal networks.

Texture Analysis and Cartographic Feature Extraction.

DTIC Science & Technology

1985-01-01

Investigations into using various image descriptors as well as developing interactive feature extraction software on the Digital Image Analysis Laboratory...system. Originator-supplied keywords: Ad-Hoc image descriptor; Bayes classifier; Bhattachryya distance; Clustering; Digital Image Analysis Laboratory

Performance of a Method to Standardize Breast Ultrasound Interpretation Using Image Processing and Case-Based Reasoning

NASA Astrophysics Data System (ADS)

André, M. P.; Galperin, M.; Berry, A.; Ojeda-Fournier, H.; O'Boyle, M.; Olson, L.; Comstock, C.; Taylor, A.; Ledgerwood, M.

Our computer-aided diagnostic (CADx) tool uses advanced image processing and artificial intelligence to analyze findings on breast sonography images. The goal is to standardize reporting of such findings using well-defined descriptors and to improve accuracy and reproducibility of interpretation of breast ultrasound by radiologists. This study examined several factors that may impact accuracy and reproducibility of the CADx software, which proved to be highly accurate and stabile over several operating conditions.

Dissecting the space-time structure of tree-ring datasets using the partial triadic analysis.

PubMed

Rossi, Jean-Pierre; Nardin, Maxime; Godefroid, Martin; Ruiz-Diaz, Manuela; Sergent, Anne-Sophie; Martinez-Meier, Alejandro; Pâques, Luc; Rozenberg, Philippe

2014-01-01

Tree-ring datasets are used in a variety of circumstances, including archeology, climatology, forest ecology, and wood technology. These data are based on microdensity profiles and consist of a set of tree-ring descriptors, such as ring width or early/latewood density, measured for a set of individual trees. Because successive rings correspond to successive years, the resulting dataset is a ring variables × trees × time datacube. Multivariate statistical analyses, such as principal component analysis, have been widely used for extracting worthwhile information from ring datasets, but they typically address two-way matrices, such as ring variables × trees or ring variables × time. Here, we explore the potential of the partial triadic analysis (PTA), a multivariate method dedicated to the analysis of three-way datasets, to apprehend the space-time structure of tree-ring datasets. We analyzed a set of 11 tree-ring descriptors measured in 149 georeferenced individuals of European larch (Larix decidua Miller) during the period of 1967-2007. The processing of densitometry profiles led to a set of ring descriptors for each tree and for each year from 1967-2007. The resulting three-way data table was subjected to two distinct analyses in order to explore i) the temporal evolution of spatial structures and ii) the spatial structure of temporal dynamics. We report the presence of a spatial structure common to the different years, highlighting the inter-individual variability of the ring descriptors at the stand scale. We found a temporal trajectory common to the trees that could be separated into a high and low frequency signal, corresponding to inter-annual variations possibly related to defoliation events and a long-term trend possibly related to climate change. We conclude that PTA is a powerful tool to unravel and hierarchize the different sources of variation within tree-ring datasets.

Protein-protein docking using region-based 3D Zernike descriptors

PubMed Central

2009-01-01

Background Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. Results We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-αRMSD ≤ 2.5 Å) within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases. Conclusion We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods. PMID:20003235

Protein-protein docking using region-based 3D Zernike descriptors.

PubMed

Venkatraman, Vishwesh; Yang, Yifeng D; Sael, Lee; Kihara, Daisuke

2009-12-09

Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-alphaRMSD < or = 2.5 A) within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases. We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods.

An Interactive Multi-instrument Database of Solar Flares

NASA Astrophysics Data System (ADS)

Sadykov, Viacheslav M.; Kosovichev, Alexander G.; Oria, Vincent; Nita, Gelu M.

2017-07-01

Solar flares are complicated physical phenomena that are observable in a broad range of the electromagnetic spectrum, from radio waves to γ-rays. For a more comprehensive understanding of flares, it is necessary to perform a combined multi-wavelength analysis using observations from many satellites and ground-based observatories. For an efficient data search, integration of different flare lists, and representation of observational data, we have developed the Interactive Multi-Instrument Database of Solar Flares (IMIDSF, https://solarflare.njit.edu/). The web-accessible database is fully functional and allows the user to search for uniquely identified flare events based on their physical descriptors and the availability of observations by a particular set of instruments. Currently, the data from three primary flare lists (Geostationary Operational Environmental Satellites, RHESSI, and HEK) and a variety of other event catalogs (Hinode, Fermi GBM, Konus-WIND, the OVSA flare catalogs, the CACTus CME catalog, the Filament eruption catalog) and observing logs (IRIS and Nobeyama coverage) are integrated, and an additional set of physical descriptors (temperature and emission measure) is provided along with an observing summary, data links, and multi-wavelength light curves for each flare event since 2002 January. We envision that this new tool will allow researchers to significantly speed up the search of events of interest for statistical and case studies.

Prediction of Chemical Function: Model Development and ...

EPA Pesticide Factsheets

The United States Environmental Protection Agency’s Exposure Forecaster (ExpoCast) project is developing both statistical and mechanism-based computational models for predicting exposures to thousands of chemicals, including those in consumer products. The high-throughput (HT) screening-level exposures developed under ExpoCast can be combined with HT screening (HTS) bioactivity data for the risk-based prioritization of chemicals for further evaluation. The functional role (e.g. solvent, plasticizer, fragrance) that a chemical performs can drive both the types of products in which it is found and the concentration in which it is present and therefore impacting exposure potential. However, critical chemical use information (including functional role) is lacking for the majority of commercial chemicals for which exposure estimates are needed. A suite of machine-learning based models for classifying chemicals in terms of their likely functional roles in products based on structure were developed. This effort required collection, curation, and harmonization of publically-available data sources of chemical functional use information from government and industry bodies. Physicochemical and structure descriptor data were generated for chemicals with function data. Machine-learning classifier models for function were then built in a cross-validated manner from the descriptor/function data using the method of random forests. The models were applied to: 1) predict chemi

Deep Eutectic Solvents as Convenient Media for Synthesis of Novel Coumarinyl Schiff Bases and Their QSAR Studies.

PubMed

Molnar, Maja; Komar, Mario; Brahmbhatt, Harshad; Babić, Jurislav; Jokić, Stela; Rastija, Vesna

2017-09-05

Deep eutectic solvents, as green and environmentally friendly media, were utilized in the synthesis of novel coumarinyl Schiff bases. Novel derivatives were synthesized from 2-((4-methyl-2-oxo-2 H -chromen-7-yl)oxy)acetohydrazide and corresponding aldehyde in choline chloride:malonic acid (1:1) based deep eutectic solvent. In these reactions, deep eutectic solvent acted as a solvent and catalyst as well. Novel Schiff bases were synthesized in high yields (65-75%) with no need for further purification, and their structures were confirmed by mass spectra, ¹H and 13 C NMR. Furthermore, their antioxidant activity was determined and compared to antioxidant activity of previously synthesized derivatives, thus investigating their structure-activity relationship utilizing quantitative structure-activity relationship QSAR studies. Calculation of molecular descriptors has been performed by DRAGON software. The best QSAR model ( R tr = 0.636; R ext = 0.709) obtained with three descriptors ( MATS3m , Mor22u , Hy ) implies that the pairs of atoms higher mass at the path length 3, three-dimensional arrangement of atoms at scattering parameter s = 21 Å - ¹, and higher number of hydrophilic groups (-OH, -NH) enhanced antioxidant activity. Electrostatic potential surface of the most active compounds showed possible regions for donation of electrons to 1,1-diphenyl-2-picryhydrazyl (DPPH) radicals.

All-Union Conference on Information Retrieval Systems and Automatic Processing of Scientific and Technical Information, 3rd, Moscow, 1967, Transactions. (Selected Articles).

ERIC Educational Resources Information Center

Air Force Systems Command, Wright-Patterson AFB, OH. Foreign Technology Div.

The role and place of the machine in scientific and technical information is explored including: basic trends in the development of information retrieval systems; preparation of engineering and scientific cadres with respect to mechanization and automation of information works; the logic of descriptor retrieval systems; the 'SETKA-3' automated…

Revising an Engineering Design Rubric: A Case Study Illustrating Principles and Practices to Ensure Technical Quality of Rubrics

ERIC Educational Resources Information Center

Goldberg, Gail Lynn

2014-01-01

This article provides a detailed account of a rubric revision process to address seven common problems to which rubrics are prone: lack of consistency and parallelism; the presence of "orphan" and "widow" words and phrases; redundancy in descriptors; inconsistency in the focus of qualifiers; limited routes to partial credit;…

Graph Theoretical Representation of Atomic Asymmetry and Molecular Chirality of Benzenoids in Two-Dimensional Space

PubMed Central

Zhao, Tanfeng; Zhang, Qingyou; Long, Hailin; Xu, Lu

2014-01-01

In order to explore atomic asymmetry and molecular chirality in 2D space, benzenoids composed of 3 to 11 hexagons in 2D space were enumerated in our laboratory. These benzenoids are regarded as planar connected polyhexes and have no internal holes; that is, their internal regions are filled with hexagons. The produced dataset was composed of 357,968 benzenoids, including more than 14 million atoms. Rather than simply labeling the huge number of atoms as being either symmetric or asymmetric, this investigation aims at exploring a quantitative graph theoretical descriptor of atomic asymmetry. Based on the particular characteristics in the 2D plane, we suggested the weighted atomic sum as the descriptor of atomic asymmetry. This descriptor is measured by circulating around the molecule going in opposite directions. The investigation demonstrates that the weighted atomic sums are superior to the previously reported quantitative descriptor, atomic sums. The investigation of quantitative descriptors also reveals that the most asymmetric atom is in a structure with a spiral ring with the convex shape going in clockwise direction and concave shape going in anticlockwise direction from the atom. Based on weighted atomic sums, a weighted F index is introduced to quantitatively represent molecular chirality in the plane, rather than merely regarding benzenoids as being either chiral or achiral. By validating with enumerated benzenoids, the results indicate that the weighted F indexes were in accordance with their chiral classification (achiral or chiral) over the whole benzenoids dataset. Furthermore, weighted F indexes were superior to previously available descriptors. Benzenoids possess a variety of shapes and can be extended to practically represent any shape in 2D space—our proposed descriptor has thus the potential to be a general method to represent 2D molecular chirality based on the difference between clockwise and anticlockwise sums around a molecule. PMID:25032832

Thermal regimes, nonnative trout, and their influences on native Bull Trout in the Upper Klamath River Basin, Oregon

USGS Publications Warehouse

Benjamin, Joseph R.; Heltzel, Jeannie; Dunham, Jason B.; Heck, Michael; Banish, Nolan P.

2016-01-01

The occurrence of fish species may be strongly influenced by a stream’s thermal regime (magnitude, frequency, variation, and timing). For instance, magnitude and frequency provide information about sublethal temperatures, variability in temperature can affect behavioral thermoregulation and bioenergetics, and timing of thermal events may cue life history events, such as spawning and migration. We explored the relationship between thermal regimes and the occurrences of native Bull Trout Salvelinus confluentus and nonnative Brook Trout Salvelinus fontinalis and Brown Trout Salmo trutta across 87 sites in the upper Klamath River basin, Oregon. Our objectives were to associate descriptors of the thermal regime with trout occurrence, predict the probability of Bull Trout occurrence, and estimate upper thermal tolerances of the trout species. We found that each species was associated with a different suite of thermal regime descriptors. Bull Trout were present at sites that were cooler, had fewer high-temperature events, had less variability, and took longer to warm. Brook Trout were also observed at cooler sites with fewer high-temperature events, but the sites were more variable and Brook Trout occurrence was not associated with a timing descriptor. In contrast, Brown Trout were present at sites that were warmer and reached higher temperatures faster, but they were not associated with frequency or variability descriptors. Among the descriptors considered, magnitude (specifically June degree-days) was the most important in predicting the probability of Bull Trout occurrence, and model predictions were strengthened by including Brook Trout occurrence. Last, all three trout species exhibited contrasting patterns of tolerating longer exposures to lower temperatures. Tolerance limits for Bull Trout were lower than those for Brook Trout and Brown Trout, with contrasts especially evident for thermal maxima. Our results confirm the value of exploring a suite of thermal regime descriptors for understanding the distribution and occurrence of fishes. Moreover, these descriptors and their relationships to fish should be considered with future changes in land use, water use, or climate.

'Putting it into words': developing the RCGP competency descriptors to include 'at-risk behaviours'.

PubMed

Jones, Tim; Tracey, Sue

2012-11-01

As part of the Royal College of General Practitioners' (RCGP) arrangements to satisfy the GMC's requirement for Work Place Based Assessment (WPBAs) a range of 12 WPBA competencies was drawn up. Further to this the RCGP produced descriptors of the behaviours that would demonstrate a trainee had gained competence in that area. Recently the RCGP have expanded the rating scale available to educational supervisors at the time of a review to allow for a finding of 'Needs Further Development (NFD) - below expectations'. In the North of Scotland Deanery it has been recognised that a number of trainees are struggling to demonstrate competency in WPBA and to complete training. Reviewing how we could help these trainees and their educational supervisors there was recognition that early identification of these trainees would assist remedial action. Additionally, having reliable indicators of behaviours associated with a trainee in difficulty would aid the assessment of a trainee as 'NFD - below expectations'. Although many reliable descriptors of 'at-risk' behaviour exist, within frameworks and systems for doctors felt to be in difficulty these systems lie outwith the WPBA competency framework. This paper describes the work undertaken in the North of Scotland Deanery to modify the original table of descriptors for the 12 WPBA competencies to include an 'NFD - below expectations'/'at-risk' behaviours column. The descriptors of behaviours associated with trainees in difficulty have been aligned to the 12 WPBA competencies and used to populate the additional column in the descriptor table. The expectation is that the expanded table of descriptors will assist both in early identification of trainees' at-risk behaviours so that formative work can be engaged in at an early stage in an attachment, and also in the objective assessment of a trainee at an educational supervisor's review if they're in difficulties.

Unsupervised automated high throughput phenotyping of RNAi time-lapse movies.

PubMed

Failmezger, Henrik; Fröhlich, Holger; Tresch, Achim

2013-10-04

Gene perturbation experiments in combination with fluorescence time-lapse cell imaging are a powerful tool in reverse genetics. High content applications require tools for the automated processing of the large amounts of data. These tools include in general several image processing steps, the extraction of morphological descriptors, and the grouping of cells into phenotype classes according to their descriptors. This phenotyping can be applied in a supervised or an unsupervised manner. Unsupervised methods are suitable for the discovery of formerly unknown phenotypes, which are expected to occur in high-throughput RNAi time-lapse screens. We developed an unsupervised phenotyping approach based on Hidden Markov Models (HMMs) with multivariate Gaussian emissions for the detection of knockdown-specific phenotypes in RNAi time-lapse movies. The automated detection of abnormal cell morphologies allows us to assign a phenotypic fingerprint to each gene knockdown. By applying our method to the Mitocheck database, we show that a phenotypic fingerprint is indicative of a gene's function. Our fully unsupervised HMM-based phenotyping is able to automatically identify cell morphologies that are specific for a certain knockdown. Beyond the identification of genes whose knockdown affects cell morphology, phenotypic fingerprints can be used to find modules of functionally related genes.

Variational mode decomposition based approach for accurate classification of color fundus images with hemorrhages

NASA Astrophysics Data System (ADS)

Lahmiri, Salim; Shmuel, Amir

2017-11-01

Diabetic retinopathy is a disease that can cause a loss of vision. An early and accurate diagnosis helps to improve treatment of the disease and prognosis. One of the earliest characteristics of diabetic retinopathy is the appearance of retinal hemorrhages. The purpose of this study is to design a fully automated system for the detection of hemorrhages in a retinal image. In the first stage of our proposed system, a retinal image is processed with variational mode decomposition (VMD) to obtain the first variational mode, which captures the high frequency components of the original image. In the second stage, four texture descriptors are extracted from the first variational mode. Finally, a classifier trained with all computed texture descriptors is used to distinguish between images of healthy and unhealthy retinas with hemorrhages. Experimental results showed evidence of the effectiveness of the proposed system for detection of hemorrhages in the retina, since a perfect detection rate was achieved. Our proposed system for detecting diabetic retinopathy is simple and easy to implement. It requires only short processing time, and it yields higher accuracy in comparison with previously proposed methods for detecting diabetic retinopathy.

Classification of melanoma lesions using sparse coded features and random forests

NASA Astrophysics Data System (ADS)

Rastgoo, Mojdeh; Lemaître, Guillaume; Morel, Olivier; Massich, Joan; Garcia, Rafael; Meriaudeau, Fabrice; Marzani, Franck; Sidibé, Désiré

2016-03-01

Malignant melanoma is the most dangerous type of skin cancer, yet it is the most treatable kind of cancer, conditioned by its early diagnosis which is a challenging task for clinicians and dermatologists. In this regard, CAD systems based on machine learning and image processing techniques are developed to differentiate melanoma lesions from benign and dysplastic nevi using dermoscopic images. Generally, these frameworks are composed of sequential processes: pre-processing, segmentation, and classification. This architecture faces mainly two challenges: (i) each process is complex with the need to tune a set of parameters, and is specific to a given dataset; (ii) the performance of each process depends on the previous one, and the errors are accumulated throughout the framework. In this paper, we propose a framework for melanoma classification based on sparse coding which does not rely on any pre-processing or lesion segmentation. Our framework uses Random Forests classifier and sparse representation of three features: SIFT, Hue and Opponent angle histograms, and RGB intensities. The experiments are carried out on the public PH2 dataset using a 10-fold cross-validation. The results show that SIFT sparse-coded feature achieves the highest performance with sensitivity and specificity of 100% and 90.3% respectively, with a dictionary size of 800 atoms and a sparsity level of 2. Furthermore, the descriptor based on RGB intensities achieves similar results with sensitivity and specificity of 100% and 71.3%, respectively for a smaller dictionary size of 100 atoms. In conclusion, dictionary learning techniques encode strong structures of dermoscopic images and provide discriminant descriptors.

Safety assessment in the urban park environment in Alborz Province, Iran.

PubMed

Oostakhan, Morteza; Babaei, Aliakbar

2013-01-01

Urban parks, as one of the recreational and sports sectors, could cause serious injuries among different ages if the safety issues in their design are not considered. These injuries can result from the equipment in the park, including play and sports equipment, or even from environmental factors, too. Lack of safety benchmark in parks will impact on the development of future proposals. In this article, attempts are made to survey the important safety factors in the urban parks including playgrounds, fitness equipment, pedestrian surface and environmental factors into a risk assessment. Hence, a checklist of safety factors was used. A Yes or No descriptor was allocated to any factor for determining safety level. The study also suggests recommendations for future planning concerning existing failures for designers. It was found that the safety level of the regional and local parks differ from each other.

A Novel/Old Modification of the First Zagreb Index.

PubMed

Ali, Akbar; Trinajstić, Nenad

2018-03-14

In the seminal paper [I. Gutman, N. Trinajstić, Chem. Phys. Lett. 1972, 17, 535-538], it was shown that total electron energy (Eπ ) of any alternant hydrocarbon depends on the sum of the squares of the degrees of the corresponding molecular graph. Nowadays, this sum is known as the first Zagreb index. In the same paper, another molecular descriptor was proved to influence Eπ , but that descriptor was never restudied explicitly. We call this descriptor as modified first Zagreb connection index and denote it by ZC1* . In this paper, chemical applicability of the molecular descriptor ZC1* is tested for the octane isomers. Some basic properties of ZC1* are also established here. Furthermore, the alkanes with maximum and minimum ZC1* values are determined from the class of all alkanes having fixed number of carbon atoms. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Novel Approach for Weed Type Classification Based on Shape Descriptors and a Fuzzy Decision-Making Method

PubMed Central

Herrera, Pedro Javier; Dorado, José.; Ribeiro, Ángela.

2014-01-01

An important objective in weed management is the discrimination between grasses (monocots) and broad-leaved weeds (dicots), because these two weed groups can be appropriately controlled by specific herbicides. In fact, efficiency is higher if selective treatment is performed for each type of infestation instead of using a broadcast herbicide on the whole surface. This work proposes a strategy where weeds are characterised by a set of shape descriptors (the seven Hu moments and six geometric shape descriptors). Weeds appear in outdoor field images which display real situations obtained from a RGB camera. Thus, images present a mixture of both weed species under varying conditions of lighting. In the presented approach, four decision-making methods were adapted to use the best shape descriptors as attributes and a choice was taken. This proposal establishes a novel methodology with a high success rate in weed species discrimination. PMID:25195854

Artificial intelligence systems based on texture descriptors for vaccine development.

PubMed

Nanni, Loris; Brahnam, Sheryl; Lumini, Alessandra

2011-02-01

The aim of this work is to analyze and compare several feature extraction methods for peptide classification that are based on the calculation of texture descriptors starting from a matrix representation of the peptide. This texture-based representation of the peptide is then used to train a support vector machine classifier. In our experiments, the best results are obtained using local binary patterns variants and the discrete cosine transform with selected coefficients. These results are better than those previously reported that employed texture descriptors for peptide representation. In addition, we perform experiments that combine standard approaches based on amino acid sequence. The experimental section reports several tests performed on a vaccine dataset for the prediction of peptides that bind human leukocyte antigens and on a human immunodeficiency virus (HIV-1). Experimental results confirm the usefulness of our novel descriptors. The matlab implementation of our approaches is available at http://bias.csr.unibo.it/nanni/TexturePeptide.zip.

Selection, application, and validation of a set of molecular descriptors for nuclear receptor ligands.

PubMed

Stewart, Eugene L; Brown, Peter J; Bentley, James A; Willson, Timothy M

2004-08-01

A methodology for the selection and validation of nuclear receptor ligand chemical descriptors is described. After descriptors for a targeted chemical space were selected, a virtual screening methodology utilizing this space was formulated for the identification of potential NR ligands from our corporate collection. Using simple descriptors and our virtual screening method, we are able to quickly identify potential NR ligands from a large collection of compounds. As validation of the virtual screening procedure, an 8, 000-membered NR targeted set and a 24, 000-membered diverse control set of compounds were selected from our in-house general screening collection and screened in parallel across a number of orphan NR FRET assays. For the two assays that provided at least one hit per set by the established minimum pEC(50) for activity, the results showed a 2-fold increase in the hit-rate of the targeted compound set over the diverse set.

Message communications of particular message types between compute nodes using DMA shadow buffers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blocksome, Michael A.; Parker, Jeffrey J.

Message communications of particular message types between compute nodes using DMA shadow buffers includes: receiving a buffer identifier specifying an application buffer having a message of a particular type for transmission to a target compute node through a network; selecting one of a plurality of shadow buffers for a DMA engine on the compute node for storing the message, each shadow buffer corresponding to a slot of an injection FIFO buffer maintained by the DMA engine; storing the message in the selected shadow buffer; creating a data descriptor for the message stored in the selected shadow buffer; injecting the datamore » descriptor into the slot of the injection FIFO buffer corresponding to the selected shadow buffer; selecting the data descriptor from the injection FIFO buffer; and transmitting the message specified by the selected data descriptor through the data communications network to the target compute node.« less

Bio-activity of aminosulfonyl ureas in the light of nucleic acid bases and DNA base pair interaction.

PubMed

Mondal Roy, Sutapa

2018-08-01

The quantum chemical descriptors based on density functional theory (DFT) are applied to predict the biological activity (log IC 50 ) of one class of acyl-CoA: cholesterol O-acyltransferase (ACAT) inhibitors, viz. aminosulfonyl ureas. ACAT are very effective agents for reduction of triglyceride and cholesterol levels in human body. Successful two parameter quantitative structure-activity relationship (QSAR) models are developed with a combination of relevant global and local DFT based descriptors for prediction of biological activity of aminosulfonyl ureas. The global descriptors, electron affinity of the ACAT inhibitors (EA) and/or charge transfer (ΔN) between inhibitors and model biosystems (NA bases and DNA base pairs) along with the local group atomic charge on sulfonyl moiety (∑Q Sul ) of the inhibitors reveals more than 90% efficacy of the selected descriptors for predicting the experimental log (IC 50 ) values. Copyright © 2018 Elsevier Ltd. All rights reserved.

Local Descriptors of Dynamic and Nondynamic Correlation.

PubMed

Ramos-Cordoba, Eloy; Matito, Eduard

2017-06-13

Quantitatively accurate electronic structure calculations rely on the proper description of electron correlation. A judicious choice of the approximate quantum chemistry method depends upon the importance of dynamic and nondynamic correlation, which is usually assesed by scalar measures. Existing measures of electron correlation do not consider separately the regions of the Cartesian space where dynamic or nondynamic correlation are most important. We introduce real-space descriptors of dynamic and nondynamic electron correlation that admit orbital decomposition. Integration of the local descriptors yields global numbers that can be used to quantify dynamic and nondynamic correlation. Illustrative examples over different chemical systems with varying electron correlation regimes are used to demonstrate the capabilities of the local descriptors. Since the expressions only require orbitals and occupation numbers, they can be readily applied in the context of local correlation methods, hybrid methods, density matrix functional theory, and fractional-occupancy density functional theory.

Conceptual DFT Descriptors of Amino Acids with Potential Corrosion Inhibition Properties Calculated with the Latest Minnesota Density Functionals

PubMed Central

Frau, Juan; Glossman-Mitnik, Daniel

2017-01-01

Amino acids and peptides have the potential to perform as corrosion inhibitors. The chemical reactivity descriptors that arise from Conceptual DFT for the twenty natural amino acids have been calculated by using the latest Minnesota family of density functionals. In order to verify the validity of the calculation of the descriptors directly from the HOMO and LUMO, a comparison has been performed with those obtained through ΔSCF results. Moreover, the active sites for nucleophilic and electrophilic attacks have been identified through Fukui function indices, the dual descriptor Δf(r) and the electrophilic and nucleophilic Parr functions. The results could be of interest as a starting point for the study of large peptides where the calculation of the radical cation and anion of each system may be computationally harder and costly. PMID:28361050

Image characterization by fractal descriptors in variational mode decomposition domain: Application to brain magnetic resonance

NASA Astrophysics Data System (ADS)

Lahmiri, Salim

2016-08-01

The main purpose of this work is to explore the usefulness of fractal descriptors estimated in multi-resolution domains to characterize biomedical digital image texture. In this regard, three multi-resolution techniques are considered: the well-known discrete wavelet transform (DWT) and the empirical mode decomposition (EMD), and; the newly introduced; variational mode decomposition mode (VMD). The original image is decomposed by the DWT, EMD, and VMD into different scales. Then, Fourier spectrum based fractal descriptors is estimated at specific scales and directions to characterize the image. The support vector machine (SVM) was used to perform supervised classification. The empirical study was applied to the problem of distinguishing between normal and abnormal brain magnetic resonance images (MRI) affected with Alzheimer disease (AD). Our results demonstrate that fractal descriptors estimated in VMD domain outperform those estimated in DWT and EMD domains; and also those directly estimated from the original image.

A new adaptive L1-norm for optimal descriptor selection of high-dimensional QSAR classification model for anti-hepatitis C virus activity of thiourea derivatives.

PubMed

Algamal, Z Y; Lee, M H

2017-01-01

A high-dimensional quantitative structure-activity relationship (QSAR) classification model typically contains a large number of irrelevant and redundant descriptors. In this paper, a new design of descriptor selection for the QSAR classification model estimation method is proposed by adding a new weight inside L1-norm. The experimental results of classifying the anti-hepatitis C virus activity of thiourea derivatives demonstrate that the proposed descriptor selection method in the QSAR classification model performs effectively and competitively compared with other existing penalized methods in terms of classification performance on both the training and the testing datasets. Moreover, it is noteworthy that the results obtained in terms of stability test and applicability domain provide a robust QSAR classification model. It is evident from the results that the developed QSAR classification model could conceivably be employed for further high-dimensional QSAR classification studies.

Singular spectrum decomposition of Bouligand-Minkowski fractal descriptors: an application to the classification of texture Images

NASA Astrophysics Data System (ADS)

Florindo, João. Batista

2018-04-01

This work proposes the use of Singular Spectrum Analysis (SSA) for the classification of texture images, more specifically, to enhance the performance of the Bouligand-Minkowski fractal descriptors in this task. Fractal descriptors are known to be a powerful approach to model and particularly identify complex patterns in natural images. Nevertheless, the multiscale analysis involved in those descriptors makes them highly correlated. Although other attempts to address this point was proposed in the literature, none of them investigated the relation between the fractal correlation and the well-established analysis employed in time series. And SSA is one of the most powerful techniques for this purpose. The proposed method was employed for the classification of benchmark texture images and the results were compared with other state-of-the-art classifiers, confirming the potential of this analysis in image classification.

Effect of number of probes and their orientation on the calculation of several compressor face distortion descriptors

NASA Technical Reports Server (NTRS)

Stoll, F.; Tremback, J. W.; Arnaiz, H. H.

1979-01-01

A study was performed to determine the effects of the number and position of total pressure probes on the calculation of five compressor face distortion descriptors. This study used three sets of 320 steady state total pressure measurements that were obtained with a special rotating rake apparatus in wind tunnel tests of a mixed-compression inlet. The inlet was a one third scale model of the inlet on a YF-12 airplane, and it was tested in the wind tunnel at representative flight conditions at Mach numbers above 2.0. The study shows that large errors resulted in the calculation of the distortion descriptors even with a number of probes that were considered adequate in the past. There were errors as large as 30 and -50 percent in several distortion descriptors for a configuration consisting of eight rakes with five equal-area-weighted probes on each rake.

Observer synthesis for a class of Takagi-Sugeno descriptor system with unmeasurable premise variable. Application to fault diagnosis

NASA Astrophysics Data System (ADS)

López-Estrada, F. R.; Astorga-Zaragoza, C. M.; Theilliol, D.; Ponsart, J. C.; Valencia-Palomo, G.; Torres, L.

2017-12-01

This paper proposes a methodology to design a Takagi-Sugeno (TS) descriptor observer for a class of TS descriptor systems. Unlike the popular approach that considers measurable premise variables, this paper considers the premise variables depending on unmeasurable vectors, e.g. the system states. This consideration covers a large class of nonlinear systems and represents a real challenge for the observer synthesis. Sufficient conditions to guarantee robustness against the unmeasurable premise variables and asymptotic convergence of the TS descriptor observer are obtained based on the H∞ approach together with the Lyapunov method. As a result, the designing conditions are given in terms of linear matrix inequalities (LMIs). In addition, sensor fault detection and isolation are performed by means of a generalised observer bank. Two numerical experiments, an electrical circuit and a rolling disc system, are presented in order to illustrate the effectiveness of the proposed method.

A multivariate approach for the study of the environmental drivers of wine production structure

NASA Astrophysics Data System (ADS)

Lorenzetti, Romina; Costantini, Edoardo A. C.; Malorgio, Giulio

2015-04-01

Vitivinicultural "terroir" is a concept referring to an area in which the collective knowledge of the interactions between environment and vitivinicultural practices develops, providing distinctive characteristics to the products. The effect of the environment components over the terroir has been already widely demonstrated. What it has not been studied yet is their possible effect on the structure of wine production. Therefore, the aim of this work was to find if environmental drivers influence the wine production structure. This kind of investigation necessarily involves a change of scale towards wide territories. We used the Italian Denomination of Origin territories, which were grouped in Macro-areas (reference scale 1:500,000) with respect of geographic proximity, environmental features, viticultural affinity and tradition. The characterization of the structure of the wine transformation industry was based on the official data reported in the wine production declarations related to the year 2008. Statistics were taken into account about general quantitative variables of wine farms, presence of associative forms, degree of vertical integration of wineries, quality orientation of wine producers, and acreage of vineyard. The environmental variables climate, soil, and vegetation vigour were selected for their direct influence on the vine growing. A second set of variables was chosen to express the effect of land morphology on viticultural management. The third one was intended to discover the possible relationships between viticultural structures and land quality, such as the indexes of sensitivity to desertification, the soil resistance to water erosion, and land vulnerability. A PCA was carried out separately for the environmental and economic data to reduce the database dimensions. The new economic and environmental synthetic descriptors were involved in three multivariate analyses: i) the correlation between economic and environmental descriptors through the non-parametric Spearman test; ii) a cluster analysis to group the Macro-areas in few homogeneous economic structures; iii) a discriminant analysis of economic clusters and environmental factors, to highlight the environmental drivers of the different wine production structures. The cluster analysis identified six systems of production and organization. Climatic, pedoclimatic, morphological mean conditions and morphological heterogeneity of Macro-areas had the most important discriminant power over the clusters. The economic structures addressed to large-scale kind of production and those with a not clear orientation were located in low hills and plains with Mediterranean climatic conditions. Lands at higher elevation and rougher morphology correlated with high quality products and structures, either made of little independent farms or cooperatives, in the highest cold wet areas, or large independent farms, on medium hill. In conclusion, for the first time it was proved that certain landscape characteristics have a significant influence over the typology of wine production structure. The result of this multivariate analyses suggest that pedo-climatic characteristics and landscape attributes care can have a strategic role on the wine industry.

Predicting Anthropogenic Noise Contributions to US Waters.

PubMed

Gedamke, Jason; Ferguson, Megan; Harrison, Jolie; Hatch, Leila; Henderson, Laurel; Porter, Michael B; Southall, Brandon L; Van Parijs, Sofie

2016-01-01

To increase understanding of the potential effects of chronic underwater noise in US waters, the National Oceanic and Atmospheric Administration (NOAA) organized two working groups in 2011, collectively called "CetSound," to develop tools to map the density and distribution of cetaceans (CetMap) and predict the contribution of human activities to underwater noise (SoundMap). The SoundMap effort utilized data on density, distribution, acoustic signatures of dominant noise sources, and environmental descriptors to map estimated temporal, spatial, and spectral contributions to background noise. These predicted soundscapes are an initial step toward assessing chronic anthropogenic noise impacts on the ocean's varied acoustic habitats and the animals utilizing them.

Effects of brand variants on smokers' choice behaviours and risk perceptions.

PubMed

Hoek, Janet; Gendall, Philip; Eckert, Christine; Kemper, Joya; Louviere, Jordan

2016-03-01

Australian tobacco companies have introduced evocative variant names that could re-create the aspirational connotations plain packaging aims to remove. To inform future regulation, we explored how brand descriptors affected smokers' responses to plain packs featuring different variant name combinations. An online survey of 254 daily smokers or social smokers aged between 18 and 34 used a within-subjects best-worst experiment to estimate the relative effects of variant names. A 2×4×4×4 design contained four attributes: quality (premium or none), taste (smooth, fine, rich or none) connotation (classic, midnight, infinite or none) and colour (red, blue, white or none). In a between-subjects component, respondents evaluated one of two alternative packs according to its perceived harm and ease of quitting. The most important variant attribute was connotation, followed by taste, colour and quality; within these attributes, the most attractive descriptors were 'classic' and 'smooth'. We identified four distinct segments that differed significantly in their sociodemographic attributes and variant preferences, although not in their perceptions of the harm or quitting ease associated with two different variants. Some descriptors significantly enhance the appeal of tobacco products among different groups of smokers and may undermine plain packaging's dissuasive intent. Policymakers should explicitly regulate variant names to avoid the 'poetry on a package' evident in Australia. Options include disallowing new descriptors, limiting the number of descriptors permitted or banning descriptors altogether. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Chemical graphs, molecular matrices and topological indices in chemoinformatics and quantitative structure-activity relationships.

PubMed

Ivanciuc, Ovidiu

2013-06-01

Chemical and molecular graphs have fundamental applications in chemoinformatics, quantitative structureproperty relationships (QSPR), quantitative structure-activity relationships (QSAR), virtual screening of chemical libraries, and computational drug design. Chemoinformatics applications of graphs include chemical structure representation and coding, database search and retrieval, and physicochemical property prediction. QSPR, QSAR and virtual screening are based on the structure-property principle, which states that the physicochemical and biological properties of chemical compounds can be predicted from their chemical structure. Such structure-property correlations are usually developed from topological indices and fingerprints computed from the molecular graph and from molecular descriptors computed from the three-dimensional chemical structure. We present here a selection of the most important graph descriptors and topological indices, including molecular matrices, graph spectra, spectral moments, graph polynomials, and vertex topological indices. These graph descriptors are used to define several topological indices based on molecular connectivity, graph distance, reciprocal distance, distance-degree, distance-valency, spectra, polynomials, and information theory concepts. The molecular descriptors and topological indices can be developed with a more general approach, based on molecular graph operators, which define a family of graph indices related by a common formula. Graph descriptors and topological indices for molecules containing heteroatoms and multiple bonds are computed with weighting schemes based on atomic properties, such as the atomic number, covalent radius, or electronegativity. The correlation in QSPR and QSAR models can be improved by optimizing some parameters in the formula of topological indices, as demonstrated for structural descriptors based on atomic connectivity and graph distance.

Many-Body Descriptors for Predicting Molecular Properties with Machine Learning: Analysis of Pairwise and Three-Body Interactions in Molecules.

PubMed

Pronobis, Wiktor; Tkatchenko, Alexandre; Müller, Klaus-Robert

2018-06-12

Machine learning (ML) based prediction of molecular properties across chemical compound space is an important and alternative approach to efficiently estimate the solutions of highly complex many-electron problems in chemistry and physics. Statistical methods represent molecules as descriptors that should encode molecular symmetries and interactions between atoms. Many such descriptors have been proposed; all of them have advantages and limitations. Here, we propose a set of general two-body and three-body interaction descriptors which are invariant to translation, rotation, and atomic indexing. By adapting the successfully used kernel ridge regression methods of machine learning, we evaluate our descriptors on predicting several properties of small organic molecules calculated using density-functional theory. We use two data sets. The GDB-7 set contains 6868 molecules with up to 7 heavy atoms of type CNO. The GDB-9 set is composed of 131722 molecules with up to 9 heavy atoms containing CNO. When trained on 5000 random molecules, our best model achieves an accuracy of 0.8 kcal/mol (on the remaining 1868 molecules of GDB-7) and 1.5 kcal/mol (on the remaining 126722 molecules of GDB-9) respectively. Applying a linear regression model on our novel many-body descriptors performs almost equal to a nonlinear kernelized model. Linear models are readily interpretable: a feature importance ranking measure helps to obtain qualitative and quantitative insights on the importance of two- and three-body molecular interactions for predicting molecular properties computed with quantum-mechanical methods.

The use of language to express thermal sensation suggests heat acclimatization by Indonesian people

NASA Astrophysics Data System (ADS)

Tochihara, Yutaka; Lee, Joo-Young; Wakabayashi, Hitoshi; Wijayanto, Titis; Bakri, Ilham; Parsons, Ken

2012-11-01

The purpose of this study was to explore whether there is evidence of heat acclimatization in the words used to express thermal sensation. A total of 458 urban Japanese and 601 Indonesians participated in a questionnaire. In addition, in a preliminary survey, 39 native English speakers in the UK participated. Our results showed that (1) for Indonesians, the closest thermal descriptor of a feeling of thermal comfort was `cool' (75%) followed by `slightly cool' (7%), `slightly cold' (5%) and `cold' (5%), while Japanese responses were distributed uniformly among descriptors `cool', `slightly cool', `neither', `slightly warm', and `warm'; (2) the closest thermal descriptors of a feeling of discomfort for Indonesians were less affected by individual thermal susceptibility (vulnerability) than those for Japanese; (3) in the cases where `cool' and `slightly cold' were imagined in the mind, the descriptors were cognized as a thermal comfortable feeling by 97% and 57% of Indonesians, respectively; (4) the most frequently voted choice endorsing hot weather was `higher than 32°C' for Indonesians and `higher than 29°C' for Japanese respondents; for cold weather, `lower than 15°C' for Japanese and `lower than 20°C' for Indonesians. In summary, the descriptor `cool' in Indonesians connotes a thermally comfortable feeling, but the inter-zone between hot and cold weather that was judged in the mind showed a upward shift when compared to that of Japanese. It is suggested that linguistic heat acclimatization exists on a cognitive level for Indonesians and is preserved in the words of thermal descriptors.

Blast and ballistic trajectories in combat casualties: a preliminary analysis using a cartesian positioning system with MDCT.

PubMed

Folio, Les R; Fischer, Tatjana; Shogan, Paul; Frew, Michael; Dwyer, Andrew; Provenzale, James M

2011-08-01

The purpose of this study is to determine the agreement with which radiologists identify wound paths in vivo on MDCT and calculate missile trajectories on the basis of Cartesian coordinates using a Cartesian positioning system (CPS). Three radiologists retrospectively identified 25 trajectories on MDCT in 19 casualties who sustained penetrating trauma in Iraq. Trajectories were described qualitatively in terms of directional path descriptors and quantitatively as trajectory vectors. Directional descriptors, trajectory angles, and angles between trajectories were calculated based on Cartesian coordinates of entrance and terminus or exit recorded in x, y image and table space (z) using a Trajectory Calculator created using spreadsheet software. The consistency of qualitative descriptor determinations was assessed in terms of frequency of observer agreement and multirater kappa statistics. Consistency of trajectory vectors was evaluated in terms of distribution of magnitude of the angles between vectors and the differences between their paraaxial and parasagittal angles. In 68% of trajectories, the observers' visual assessment of qualitative descriptors was congruent. Calculated descriptors agreed across observers in 60% of the trajectories. Estimated kappa also showed good agreement (0.65-0.79, p < 0.001); 70% of calculated paraaxial and parasagittal angles were within 20° across observers, and 61.3% of angles between trajectory vectors were within 20° across observers. Results show agreement of visually assessed and calculated qualitative descriptors and trajectory angles among observers. The Trajectory Calculator describes trajectories qualitatively similar to radiologists' visual assessment, showing the potential feasibility of automated trajectory analysis.

Ability of bottle cap color to facilitate accurate glaucoma patient-physician communication regarding medication identity

PubMed Central

Dave, Pujan; Villarreal, Guadalupe; Friedman, David S.; Kahook, Malik Y.; Ramulu, Pradeep Y.

2015-01-01

Objective To determine the accuracy of patient-physician communication regarding topical ophthalmic medication use based on bottle cap color, particularly amongst individuals who may have acquired color vision deficiency from glaucoma. Design Cross-sectional, clinical study. Participants Patients ≥ 18 years old with primary open-angle, primary angle-closure, pseudoexfoliation, or pigment dispersion glaucoma, bilateral visual acuity of 20/400 or better, and no concurrent conditions that may affect color vision. Methods One hundred patients provided color descriptions of 11 distinct medication bottle caps. Patient-produced color descriptors were then presented to three physicians. Each physician matched each color descriptor to the medication they thought the descriptor was describing. Main Outcome Measures Frequency of patient-physician agreement, occurring when all three physicians accurately matched the patient-produced color descriptor to the correct medication. Multivariate regression models evaluated whether patient-physician agreement decreased with degree of better-eye visual field (VF) damage, color descriptor heterogeneity, and/or color vision deficiency, as determined by Hardy-Rand-Rittler (HRR) score and the Lanthony D15 testing index (D15 CCI). Results Subjects had a mean age of 69 (±11) years, with mean VF mean deviation of −4.7 (±6.0) and −10.9 (±8.4) dB in the better- and worse-seeing eyes, respectively. Patients produced 102 unique color descriptors to describe the colors of the 11 tested bottle caps. Among individual patients, the mean number of medications demonstrating patient-physician agreement was 6.1/11 (55.5%). Agreement was less than 15% for 4 medications (prednisolone acetate [generic], betaxolol HCl [Betoptic], brinzolamide/brimonidine [Simbrinza], and latanoprost [Xalatan]). Lower HRR scores and higher D15 CCI (both indicating worse color vision) were associated with greater VF damage (p<0.001). Extent of color vision deficiency and color descriptor heterogeneity were the only significant predictors of patient-physician agreement in multivariate models (odds of agreement = 0.90 per 1 point decrement in HRR score, p<0.001; odds of agreement = 0.30 for medications exhibiting high heterogeneity [≥ 11 descriptors], p=0.007). Conclusions Physician understanding of patient medication usage based solely on bottle cap color is frequently incorrect, particularly in glaucoma patients who may have color vision deficiency. Errors based on communication using bottle cap color alone may be common and could lead to confusion and harm. PMID:26260280

Neural network-based feature point descriptors for registration of optical and SAR images

NASA Astrophysics Data System (ADS)

Abulkhanov, Dmitry; Konovalenko, Ivan; Nikolaev, Dmitry; Savchik, Alexey; Shvets, Evgeny; Sidorchuk, Dmitry

2018-04-01

Registration of images of different nature is an important technique used in image fusion, change detection, efficient information representation and other problems of computer vision. Solving this task using feature-based approaches is usually more complex than registration of several optical images because traditional feature descriptors (SIFT, SURF, etc.) perform poorly when images have different nature. In this paper we consider the problem of registration of SAR and optical images. We train neural network to build feature point descriptors and use RANSAC algorithm to align found matches. Experimental results are presented that confirm the method's effectiveness.

Periodic table-based descriptors to encode cytotoxicity profile of metal oxide nanoparticles: a mechanistic QSTR approach.

PubMed

Kar, Supratik; Gajewicz, Agnieszka; Puzyn, Tomasz; Roy, Kunal; Leszczynski, Jerzy

2014-09-01

Nanotechnology has evolved as a frontrunner in the development of modern science. Current studies have established toxicity of some nanoparticles to human and environment. Lack of sufficient data and low adequacy of experimental protocols hinder comprehensive risk assessment of nanoparticles (NPs). In the present work, metal electronegativity (χ), the charge of the metal cation corresponding to a given oxide (χox), atomic number and valence electron number of the metal have been used as simple molecular descriptors to build up quantitative structure-toxicity relationship (QSTR) models for prediction of cytotoxicity of metal oxide NPs to bacteria Escherichia coli. These descriptors can be easily obtained from molecular formula and information acquired from periodic table in no time. It has been shown that a simple molecular descriptor χox can efficiently encode cytotoxicity of metal oxides leading to models with high statistical quality as well as interpretability. Based on this model and previously published experimental results, we have hypothesized the most probable mechanism of the cytotoxicity of metal oxide nanoparticles to E. coli. Moreover, the required information for descriptor calculation is independent of size range of NPs, nullifying a significant problem that various physical properties of NPs change for different size ranges. Copyright © 2014 Elsevier Inc. All rights reserved.

An infrastructure to mine molecular descriptors for ligand selection on virtual screening.

PubMed

Seus, Vinicius Rosa; Perazzo, Giovanni Xavier; Winck, Ana T; Werhli, Adriano V; Machado, Karina S

2014-01-01

The receptor-ligand interaction evaluation is one important step in rational drug design. The databases that provide the structures of the ligands are growing on a daily basis. This makes it impossible to test all the ligands for a target receptor. Hence, a ligand selection before testing the ligands is needed. One possible approach is to evaluate a set of molecular descriptors. With the aim of describing the characteristics of promising compounds for a specific receptor we introduce a data warehouse-based infrastructure to mine molecular descriptors for virtual screening (VS). We performed experiments that consider as target the receptor HIV-1 protease and different compounds for this protein. A set of 9 molecular descriptors are taken as the predictive attributes and the free energy of binding is taken as a target attribute. By applying the J48 algorithm over the data we obtain decision tree models that achieved up to 84% of accuracy. The models indicate which molecular descriptors and their respective values are relevant to influence good FEB results. Using their rules we performed ligand selection on ZINC database. Our results show important reduction in ligands selection to be applied in VS experiments; for instance, the best selection model picked only 0.21% of the total amount of drug-like ligands.

Characterization of Mixtures. Part 2: QSPR Models for Prediction of Excess Molar Volume and Liquid Density Using Neural Networks.

PubMed

Ajmani, Subhash; Rogers, Stephen C; Barley, Mark H; Burgess, Andrew N; Livingstone, David J

2010-09-17

In our earlier work, we have demonstrated that it is possible to characterize binary mixtures using single component descriptors by applying various mixing rules. We also showed that these methods were successful in building predictive QSPR models to study various mixture properties of interest. Here in, we developed a QSPR model of an excess thermodynamic property of binary mixtures i.e. excess molar volume (V(E) ). In the present study, we use a set of mixture descriptors which we earlier designed to specifically account for intermolecular interactions between the components of a mixture and applied successfully to the prediction of infinite-dilution activity coefficients using neural networks (part 1 of this series). We obtain a significant QSPR model for the prediction of excess molar volume (V(E) ) using consensus neural networks and five mixture descriptors. We find that hydrogen bond and thermodynamic descriptors are the most important in determining excess molar volume (V(E) ), which is in line with the theory of intermolecular forces governing excess mixture properties. The results also suggest that the mixture descriptors utilized herein may be sufficient to model a wide variety of properties of binary and possibly even more complex mixtures. Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Notes on quantitative structure-properties relationships (QSPR) (1): A discussion on a QSPR dimensionality paradox (QSPR DP) and its quantum resolution.

PubMed

Carbó-Dorca, Ramon; Gallegos, Ana; Sánchez, Angel J

2009-05-01

Classical quantitative structure-properties relationship (QSPR) statistical techniques unavoidably present an inherent paradoxical computational context. They rely on the definition of a Gram matrix in descriptor spaces, which is used afterwards to reduce the original dimension via several possible kinds of algebraic manipulations. From there, effective models for the computation of unknown properties of known molecular structures are obtained. However, the reduced descriptor dimension causes linear dependence within the set of discrete vector molecular representations, leading to positive semi-definite Gram matrices in molecular spaces. To resolve this QSPR dimensionality paradox (QSPR DP) here is proposed to adopt as starting point the quantum QSPR (QQSPR) computational framework perspective, where density functions act as infinite dimensional descriptors. The fundamental QQSPR equation, deduced from employing quantum expectation value numerical evaluation, can be approximately solved in order to obtain models exempt of the QSPR DP. The substitution of the quantum similarity matrix by an empirical Gram matrix in molecular spaces, build up with the original non manipulated discrete molecular descriptor vectors, permits to obtain classical QSPR models with the same characteristics as in QQSPR, that is: possessing a certain degree of causality and explicitly independent of the descriptor dimension. 2008 Wiley Periodicals, Inc.

Qualitative spatial logic descriptors from 3D indoor scenes to generate explanations in natural language.

PubMed

Falomir, Zoe; Kluth, Thomas

2017-06-24

The challenge of describing 3D real scenes is tackled in this paper using qualitative spatial descriptors. A key point to study is which qualitative descriptors to use and how these qualitative descriptors must be organized to produce a suitable cognitive explanation. In order to find answers, a survey test was carried out with human participants which openly described a scene containing some pieces of furniture. The data obtained in this survey are analysed, and taking this into account, the QSn3D computational approach was developed which uses a XBox 360 Kinect to obtain 3D data from a real indoor scene. Object features are computed on these 3D data to identify objects in indoor scenes. The object orientation is computed, and qualitative spatial relations between the objects are extracted. These qualitative spatial relations are the input to a grammar which applies saliency rules obtained from the survey study and generates cognitive natural language descriptions of scenes. Moreover, these qualitative descriptors can be expressed as first-order logical facts in Prolog for further reasoning. Finally, a validation study is carried out to test whether the descriptions provided by QSn3D approach are human readable. The obtained results show that their acceptability is higher than 82%.

Classification of Strawberry Fruit Shape by Machine Learning

NASA Astrophysics Data System (ADS)

Ishikawa, T.; Hayashi, A.; Nagamatsu, S.; Kyutoku, Y.; Dan, I.; Wada, T.; Oku, K.; Saeki, Y.; Uto, T.; Tanabata, T.; Isobe, S.; Kochi, N.

2018-05-01

Shape is one of the most important traits of agricultural products due to its relationships with the quality, quantity, and value of the products. For strawberries, the nine types of fruit shape were defined and classified by humans based on the sampler patterns of the nine types. In this study, we tested the classification of strawberry shapes by machine learning in order to increase the accuracy of the classification, and we introduce the concept of computerization into this field. Four types of descriptors were extracted from the digital images of strawberries: (1) the Measured Values (MVs) including the length of the contour line, the area, the fruit length and width, and the fruit width/length ratio; (2) the Ellipse Similarity Index (ESI); (3) Elliptic Fourier Descriptors (EFDs), and (4) Chain Code Subtraction (CCS). We used these descriptors for the classification test along with the random forest approach, and eight of the nine shape types were classified with combinations of MVs + CCS + EFDs. CCS is a descriptor that adds human knowledge to the chain codes, and it showed higher robustness in classification than the other descriptors. Our results suggest machine learning's high ability to classify fruit shapes accurately. We will attempt to increase the classification accuracy and apply the machine learning methods to other plant species.

Molecular structure and gas chromatographic retention behavior of the components of Ylang-Ylang oil.

PubMed

Olivero, J; Gracia, T; Payares, P; Vivas, R; Díaz, D; Daza, E; Geerlings, P

1997-05-01

Using quantitative structure-retention relationships (QSRR) methodologies the Kovats gas chromatographic retention indices for both apolar (DB-1) and polar (DB-Wax) columns for 48 compounds from Ylang-Ylang essential oil were empirically predicted from calculated and experimental data on molecular structure. Topological, geometric, and electronic descriptors were obtained for model generation. Relationships between descriptors and the retention data reported were established by linear multiple regression, giving equations that can be used to predict the Kovats indices for compounds present in essential oils, both in DB-1 and DB-Wax columns. Factor analysis was performed to interpret the meaning of the descriptors included in the models. The prediction model for the DB-1 column includes descriptors such as Randic's first-order connectivity index (1X), the molecular surface (MSA), the sum of the atomic charge on all the hydrogens (QH), Randic's third-order connectivity index (3X) and the molecular electronegativity (chi). The prediction model for the DB-Wax column includes the first three descriptors mentioned for the DB-1 column (1X, MSA and QH) and the most negative charge (MNC), the global softness (S), and the difference between Randic's and Kier and Hall's third-order connectivity indexes (3X-3XV).

Learning structure-property relationship in crystalline materials: A study of lanthanide-transition metal alloys

NASA Astrophysics Data System (ADS)

Pham, Tien-Lam; Nguyen, Nguyen-Duong; Nguyen, Van-Doan; Kino, Hiori; Miyake, Takashi; Dam, Hieu-Chi

2018-05-01

We have developed a descriptor named Orbital Field Matrix (OFM) for representing material structures in datasets of multi-element materials. The descriptor is based on the information regarding atomic valence shell electrons and their coordination. In this work, we develop an extension of OFM called OFM1. We have shown that these descriptors are highly applicable in predicting the physical properties of materials and in providing insights on the materials space by mapping into a low embedded dimensional space. Our experiments with transition metal/lanthanide metal alloys show that the local magnetic moments and formation energies can be accurately reproduced using simple nearest-neighbor regression, thus confirming the relevance of our descriptors. Using kernel ridge regressions, we could accurately reproduce formation energies and local magnetic moments calculated based on first-principles, with mean absolute errors of 0.03 μB and 0.10 eV/atom, respectively. We show that meaningful low-dimensional representations can be extracted from the original descriptor using descriptive learning algorithms. Intuitive prehension on the materials space, qualitative evaluation on the similarities in local structures or crystalline materials, and inference in the designing of new materials by element substitution can be performed effectively based on these low-dimensional representations.

Message passing with a limited number of DMA byte counters

DOEpatents

Blocksome, Michael [Rochester, MN; Chen, Dong [Croton on Hudson, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Kumar, Sameer [White Plains, NY; Parker, Jeffrey J [Rochester, MN

2011-10-04

A method for passing messages in a parallel computer system constructed as a plurality of compute nodes interconnected as a network where each compute node includes a DMA engine but includes only a limited number of byte counters for tracking a number of bytes that are sent or received by the DMA engine, where the byte counters may be used in shared counter or exclusive counter modes of operation. The method includes using rendezvous protocol, a source compute node deterministically sending a request to send (RTS) message with a single RTS descriptor using an exclusive injection counter to track both the RTS message and message data to be sent in association with the RTS message, to a destination compute node such that the RTS descriptor indicates to the destination compute node that the message data will be adaptively routed to the destination node. Using one DMA FIFO at the source compute node, the RTS descriptors are maintained for rendezvous messages destined for the destination compute node to ensure proper message data ordering thereat. Using a reception counter at a DMA engine, the destination compute node tracks reception of the RTS and associated message data and sends a clear to send (CTS) message to the source node in a rendezvous protocol form of a remote get to accept the RTS message and message data and processing the remote get (CTS) by the source compute node DMA engine to provide the message data to be sent.

Analyzing Molecular Clouds with the Spectral Correlation Function

NASA Astrophysics Data System (ADS)

Rosolowsky, E. W.; Goodman, A. A.; Williams, J. P.; Wilner, D. J.

1997-12-01

The Spectral Correlation Function (SCF) is a new data analysis algorithm that measures how the properites of spectra vary from position to position in a spectral-line map. For each spectrum in a data cube, the SCF measures the ``difference" between that spectrum and a specified subset of its neighbors. This algorithm is intended for use on both simulated and observed position-position-velocity data cubes. In initial tests of the SCF, we have shown that a histogram of the SCF for a map is a good descriptor of the spatial-velocity distribution of material. In one test, we compare the SCF distributions for: 1) a real data cube; 2) a cube made from the real cube's spectra with randomized positions; and 3) the results of a preliminary MHD simulation by Gammie, Ostriker, and Stone. The results of the test show that the real cloud and the simulation are much closer to each other in their SCF distributions than is either to the randomized cube. We are now in the process of applying the SCF to a larger set of observed and simulated data cubes. Our ultimate aim is to use the SCF both on its own, as a descriptor of the spatial-kinetic properties of interstellar gas, and also as a tool for evaluating how well simulations resemble observations. Our expectation is that the SCF will be more discriminatory (less likely to produce a false match) than the data cube descriptors currently available.

Furthering the investigation of eruption styles through quantitative shape analyses of volcanic ash particles

NASA Astrophysics Data System (ADS)

Nurfiani, D.; Bouvet de Maisonneuve, C.

2018-04-01

Volcanic ash morphology has been quantitatively investigated for various aims such as studying the settling velocity of ash for modelling purposes and understanding the fragmentation processes at the origin of explosive eruptions. In an attempt to investigate the usefulness of ash morphometry for monitoring purposes, we analyzed the shape of volcanic ash particles through a combination of (1) traditional shape descriptors such as solidity, convexity, axial ratio and form factor and (2) fractal analysis using the Euclidean Distance transform (EDT) method. We compare ash samples from the hydrothermal eruptions of Iwodake (Japan) in 2013, Tangkuban Perahu (Indonesia) in 2013 and Marapi (Sumatra, Indonesia) in 2015, the dome explosions of Merapi (Java, Indonesia) in 2013, the Vulcanian eruptions of Merapi in 2010 and Tavurvur (Rabaul, Papaua New Guinea) in 2014, and the Plinian eruption of Kelud (Indonesia) in 2014. Particle size and shape measurements were acquired from a Particle Size Analyzer with a microscope camera attached to the instrument. Clear differences between dense/blocky particles from hydrothermal or dome explosions and vesicular particles produced by the fragmentation of gas-bearing molten magma are well highlighted by conventional shape descriptors and the fractal method. In addition, subtle differences between dense/blocky particles produced by hydrothermal explosions, dome explosions, or quench granulation during phreatomagmatic eruptions can be evidenced with the fractal method. The combination of shape descriptors and fractal analysis is therefore potentially able to distinguish between juvenile and non-juvenile magma, which is of importance for eruption monitoring.

Human impacts affect tree community features of 20 forest fragments of a vanishing neotropical hotspot.

PubMed

Pereira, José Aldo Alves; de Oliveira-Filho, Ary Teixeira; Eisenlohr, Pedro V; Miranda, Pedro L S; de Lemos Filho, José Pires

2015-02-01

The loss in forest area due to human occupancy is not the only threat to the remaining biodiversity: forest fragments are susceptible to additional human impact. Our aim was to investigate the effect of human impact on tree community features (species composition and abundance, and structural descriptors) and check if there was a decrease in the number of slender trees, an increase in the amount of large trees, and also a reduction in the number of tree species that occur in 20 fragments of Atlantic montane semideciduous forest in southeastern Brazil. We produced digital maps of each forest fragment using Landsat 7 satellite images and processed the maps to obtain morphometric variables. We used investigative questionnaires and field observations to survey the history of human impact. We then converted the information into scores given to the extent, severity, and duration of each impact, including proportional border area, fire, trails, coppicing, logging, and cattle, and converted these scores into categorical levels. We used linear models to assess the effect of impacts on tree species abundance distribution and stand structural descriptors. Part of the variation in floristic patterns was significantly correlated to the impacts of fire, logging, and proportional border area. Structural descriptors were influenced by cattle and outer roads. Our results provided, for the first time, strong evidence that tree species occurrence and abundance, and forest structure of Atlantic seasonal forest fragments respond differently to various modes of disturbance by humans.

Digital image modification detection using color information and its histograms.

PubMed

Zhou, Haoyu; Shen, Yue; Zhu, Xinghui; Liu, Bo; Fu, Zigang; Fan, Na

2016-09-01

The rapid development of many open source and commercial image editing software makes the authenticity of the digital images questionable. Copy-move forgery is one of the most widely used tampering techniques to create desirable objects or conceal undesirable objects in a scene. Existing techniques reported in the literature to detect such tampering aim to improve the robustness of these methods against the use of JPEG compression, blurring, noise, or other types of post processing operations. These post processing operations are frequently used with the intention to conceal tampering and reduce tampering clues. A robust method based on the color moments and other five image descriptors is proposed in this paper. The method divides the image into fixed size overlapping blocks. Clustering operation divides entire search space into smaller pieces with similar color distribution. Blocks from the tampered regions will reside within the same cluster since both copied and moved regions have similar color distributions. Five image descriptors are used to extract block features, which makes the method more robust to post processing operations. An ensemble of deep compositional pattern-producing neural networks are trained with these extracted features. Similarity among feature vectors in clusters indicates possible forged regions. Experimental results show that the proposed method can detect copy-move forgery even if an image was distorted by gamma correction, addictive white Gaussian noise, JPEG compression, or blurring. Copyright © 2016. Published by Elsevier Ireland Ltd.

Proposing priorities of intervention for the recovery of native fish populations using hierarchical ranking of environmental and exotic species impact.

PubMed

Aschonitis, V G; Gavioli, A; Lanzoni, M; Fano, E A; Feld, C; Castaldelli, G

2018-03-15

The freshwater populations of native fish species (Ns) have reached critical levels in many parts of the world due to combined habitat deterioration by human interventions and exotic fish species (Es) invasions. These alarming conditions require combined and well-designed interventions for restoring environmental quality and restricting Es invasion. The aim of the study is to propose a method to design spatially explicit priorities of intervention for the recovery of Ns populations in highly impacted freshwater systems by exotic multi-species invasion and water quality (WQ) degradation. WQ and Es are used as Ns descriptors, which require intervention. The method uses gradient analysis (ordination method of Canonical Correspondence Analysis) for assessing the weights of Ns descriptors' effects, which are further used to develop weighted severity indices; the severity index of WQ (Swq) and Es invasion (Se), respectively. Swq and Se are further merged to one combined total severity index St. The proposed method provides a) a ranking of the sites, based on the values of S t , which denotes the priority for combined intervention in space and can be visualized in maps, b) a ranking of the most important Ns descriptors for each site to perform site-specific interventions, and c) Es rankings based on their potential threat on Ns for species-specific interventions. WQ, Es and Ns data from 208 sampling sites located in the Emilia-Romagna Region (Northern Italy) were used as a case study for the presentation of the proposed method. The application of the method showed that the north and northwestern lowland areas of Emilia-Romagna region presented the higher priority for intervention since the Ns of these areas are the most impacted from combined Es invasions and WQ degradation. Specific Es belonging to cyprinids, which are mostly responsible for the decline of aquatic vegetation and the increase of water turbidity, and a top Es predator (Wels catfish) were mostly present in these areas. Additionally, the most important WQ stressors of Ns were found to be COD, BOD and temperature that are all connected to oxygen depletion. The aforementioned conditions in the areas described by high priority for intervention can be used as a basis for the development of specific Ns conservation practices targeting the containment of the most harmful Es, the restoration of aquatic vegetation and the improvement of oxygen conditions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Descriptive attributes used in the characterization of stingless bees (Apidae: Meliponini) in rural populations of the Atlantic forest (Misiones-Argentina)

PubMed Central

2012-01-01

Abstract Background Human beings employ a combination of morphological, sensorial, utilitarian, cultural and ecological characters when they identify and classify organisms. Ethnotaxonomy has provided a store of information about the characters cultures employ when they identify and classify a vast diversity of taxonomic groups. Nevertheless, some more research is needed to provide a comparison of the characters employed in the description of taxons, and an analysis of the extent to which those descriptors are represented. Stingless bees constitute a diverse group of social insects that have been widely studied from an ethnobiological perspective due to their utilitarian and cultural importance. The objective of this study is to identify the elements local people consider when characterizing stingless bees, and how important these elements are in the study of local classifications. Methods The methodology used involves semi-structured interviews and trips with the informants to rural areas. Locally known ethnospecies are characterized, descriptive traits and salient criteria used in those characterizations are identified, and the frequency of reference of descriptive traits and salient criteria are estimated. Besides, the descriptive traits used for each ethnospecies are compared, and the contribution of the characterizations as a heuristic strategy in the study of folk classification systems is analyzed. Results The use of 19 biological descriptors (grouped according to 4 salient criteria) and of comparisons among ethnospecies was found. Results suggest the existence of group and specific descriptors. Researchers identified which ethnospecies are considered similar, how less important traits contribute to descriptions, the relation between specific descriptors and ethnospecies, the presence of cognitive prototypes, and the most relevant salient properties from the emic perspective. Conclusions The estimated importance of attributes descriptors allowed us to identify the spectrum of salient properties relevant from the emic perspective to characterize the stingless bees. In this sense, the analysis proposed here is useful to study folk taxonomy in culturally heterogeneous groups or multicultural regions, where the linguistic elements usually employed cannot be applied. Resumen Antecedentes Los seres humanos, al identificar y clasificar a los organismos emplean una combinación de características morfológicas, sensoriales, utilitarias, culturales y ecológicas. Entre los aportes generados desde la etnotaxonomía, se ha obtenido información sobre los caracteres utilizados para identificar y clasificar una gran diversidad de grupos taxonómicos. Sin embargo, aún faltan trabajos donde se comparen los caracteres utilizados en las descripciones de taxones y se analice en qué medida estos descriptores se encuentran representados. Las abejas sin aguijón conforman un diverso grupo de insectos sociales que han sido estudiadas desde la perspectiva etnobiológica, dada su importancia utilitaria y cultural. Los interrogantes que guían este trabajo son ¿Qué elementos tienen en cuenta los pobladores para caracterizar a las abejas sin aguijón? y ¿Qué importancia revisten los mismos en el estudio de las clasificaciones locales? Métodos Se realizaron entrevistas semiestructuradas y recorridos en áreas rurales con los informantes. Se caracterizan a las etnoespecies conocidas localmente; se identifican los atributos descriptores y los criterios emergentes utilizados para dichas caracterizaciones; y se estima la frecuencia de citas de los atributos descriptores y criterios emergentes. Por otra parte, se comparan los atributos descriptores empleados para cada etnoespecie y se analiza el aporte de las caracterizaciones como estrategia heurística en el estudio de los sistemas de clasificación folclóricos. Resultados Se halló el empleo de 19 descriptores biológicos (que fueron agrupados en 4 criterios emergentes) y de comparaciones entre etnoespecies. Los resultados sugieren la existencia de descriptores de grupo y descriptores específicos. Se identificaron cuales etnoespecies son consideradas similares, cómo contribuyen a las descripciones los atributos de menor peso, la relación entre los descriptores específicos y las etnoespecies, la presencia de prototipos cognitivos, así como las propiedades emergentes más relevantes desde la perspectiva émica. Conclusiones La importancia estimada de los atributos descriptores nos ha permitido identificar el espectro de propiedades emergentes que son relevantes desde la perspectiva emic para caracterizar las abejas sin aguijón. En este sentido el análisis aquí propuesto es de utilidad para estudiar taxonomías folclóricas en grupos heterogéneos culturalmente o en regiones pluriculturales, donde los elementos lingüísticos usualmente empleados no son aplicables. PMID:22330012

Re-defining the characteristics of environmental volunteering: Creating a typology of community-scale green infrastructure.

PubMed

Jerome, Gemma; Mell, Ian; Shaw, Dave

2017-10-01

One way to engage people with green infrastructure (GI) is as environmental volunteers. Previous studies explored the nature of such groups/projects in terms of the benefits they deliver such as their impact on levels of social capital within a pre-defined community. However, existing literature contributes little to our understanding of the composition, characteristics and mechanisms used to form and maintain these groups. As such, it is difficult to establish the influencing factors determining the capacity of a group to sustain its provision over time. This paper serves to offer a more nuanced understanding of local-scale environmental stewardship by outlining the diversity of volunteer-led GI activities observed at the community-scale. Evidence presented from a desk-based examination of observable activity within The Mersey area Forest in North-West England represents a re-conceptualisation of existing definitions of Community-Scale GI (CSGI). Using thematic criteria, the paper clusters characteristics into key classification affecting group dynamics, composition and objectives. Initial findings identified the following categories as being significant descriptors for community-scale green infrastructure: status, location, timeframe, membership, activity focus, governance, resources and recognition, and communications. Thus, we classify four distinct types of group engaged in voluntary activity contributing to local level GI creation and long-term management: 'Formal Group (Active), Formal Group (Inactive), Formal Project and Informal Group. Creating a nuanced typology of CSGI provides further opportunities to analysis the creation and long-term management of GI at a site, neighbourhood and city-scale. In turn, this contributes to our understanding of how multiple actors remain engaged in the decision-making processes of GI management and maintenance. Copyright © 2017. Published by Elsevier Inc.

Descriptor Fingerprints and Their Application to WhiteWine Clustering and Discrimination.

NASA Astrophysics Data System (ADS)

Bangov, I. P.; Moskovkina, M.; Stojanov, B. P.

2018-03-01

This study continues the attempt to use the statistical process for a large-scale analytical data. A group of 3898 white wines, each with 11 analytical laboratory benchmarks was analyzed by a fingerprint similarity search in order to be grouped into separate clusters. A characterization of the wine's quality in each individual cluster was carried out according to individual laboratory parameters.

The Use of Descriptors with Exemplar and Model Answers to Improve Quality of Students' Narrative Writing in English French and Arabic

ERIC Educational Resources Information Center

Somba, Anne W.; Obura, Ger; Njuguna, Margaret; Itevete, Boniface; Mulwa, Jones; Wandera, Nooh

2015-01-01

The importance of writing skills in enhancing student performance in language exams and even other subject areas is widely acknowledged. At Jaffery secondary, the approach to the teaching of writing has generally been to use three approaches: product-based approach with focus on what the students composed; process-based approach that is focused on…

Content and ratings of teen-rated video games.

PubMed

Haninger, Kevin; Thompson, Kimberly M

2004-02-18

Children's exposure to violence, blood, sexual themes, profanity, substances, and gambling in the media remains a source of public health concern. However, content in video games played by older children and adolescents has not been quantified or compared with the rating information provided to consumers by the Entertainment Software Rating Board (ESRB). To quantify and characterize the content in video games rated T (for "Teen") and to measure the agreement between the content observed in game play and the ESRB-assigned content descriptors displayed on the game box. We created a database of all 396 T-rated video game titles released on the major video game consoles in the United States by April 1, 2001, to identify the distribution of games by genre and to characterize the distribution of ESRB-assigned content descriptors. We randomly sampled 80 video game titles (which included 81 games because 1 title included 2 separate games), played each game for at least 1 hour, quantitatively assessed the content, and compared the content we observed with the content descriptors assigned by the ESRB. Depictions of violence, blood, sexual themes, gambling, and alcohol, tobacco, or other drugs; whether injuring or killing characters is rewarded or is required to advance in the game; characterization of gender associated with sexual themes; and use of profanity in dialogue, lyrics, or gestures. Analysis of all content descriptors assigned to the 396 T-rated video game titles showed 373 (94%) received content descriptors for violence, 102 (26%) for blood, 60 (15%) for sexual themes, 57 (14%) for profanity, 26 (7%) for comic mischief, 6 (2%) for substances, and none for gambling. In the random sample of 81 games we played, we found that 79 (98%) involved intentional violence for an average of 36% of game play, 73 (90%) rewarded or required the player to injure characters, 56 (69%) rewarded or required the player to kill, 34 (42%) depicted blood, 22 (27%) depicted sexual themes, 22 (27%) contained profanity, 12 (15%) depicted substances, and 1 (1%) involved gambling. Our observations of 81 games match the ESRB content descriptors for violence in 77 games (95%), for blood in 22 (27%), for sexual themes in 16 (20%), for profanity in 14 (17%), and for substances in 1 (1%). Games were significantly more likely to depict females partially nude or engaged in sexual behaviors than males. Overall, we identified 51 observations of content that could warrant a content descriptor in 39 games (48%) in which the ESRB had not assigned a content descriptor. We found that the ESRB assigned 7 content descriptors for 7 games (9%) in which we did not observe the content indicated within 1 hour of game play. Content analysis suggests a significant amount of content in T-rated video games that might surprise adolescent players and their parents given the presence of this content in games without ESRB content descriptors. Physicians and parents should be aware that popular T-rated video games may be a source of exposure to a wide range of unexpected content.

A Community Database of Quartz Microstructures: Can we make measurements that constrain rheology?

NASA Astrophysics Data System (ADS)

Toy, Virginia; Peternell, Mark; Morales, Luiz; Kilian, Ruediger

2014-05-01

Rheology can be explored by performing deformation experiments, and by examining resultant microstructures and textures as links to naturally deformed rocks. Certain deformation processes are assumed to result in certain microstructures or textures, of which some might be uniquely indicative, while most cannot be unequivocally used to interpret the deformation mechanism and hence rheology. Despite our lack of a sufficient understanding of microstructure and texture forming processes, huge advances in texture measurements and quantification of microstructural parameters have been made. Unfortunately, there are neither standard procedures nor a common consensus on interpretation of many parameters (e.g. texture, grain size, shape preferred orientation). Textures (crystallographic preferred orientations) have been extensively correlated to the interpretation of deformation mechanisms. For example the strength of textures can be measured either from the orientation distribution function (e.g. the J-index (Bunge, 1983) or texture entropy (Hielscher et al., 2007) or via the intensity of polefigures. However, there are various ways to identify a representative volume, to measure, to process the data and to calculate an odf and texture descriptors, which restricts their use as a comparative and diagnostic measurement. Microstructural parameters such as grain size, grain shape descriptors and fabric descriptors are similarly used to deduce and quantify deformation mechanisms. However there is very little consensus on how to measure and calculate some of these very important parameters, e.g. grain size which makes comparison of a vast amount of precious data in the literature very difficult. We propose establishing a community database of a standard set of such measurements, made using typical samples of different types of quartz rocks through standard methods of microstructural and texture quantification. We invite suggestions and discussion from the community about the worth of proposed parameters, methodology and usefulness and willingness to contribute to a database with free access of the community. We further invite institutions to participate on a benchmark analysis of a set of 'standard' thin sections. Bunge, H.J. 1983, Texture Analysis in Materials Science: mathematical methods. Butterworth-Heinemann, 593pp. Hielscher, R., Schaeben, H., Chateigner, D., 2007, On the entropy to texture index relationship in quantitative texture analysis: Journal of Applied Crystallography 40, 371-375.

Quantum chemistry in environmental pesticide risk assessment.

PubMed

Villaverde, Juan J; López-Goti, Carmen; Alcamí, Manuel; Lamsabhi, Al Mokhtar; Alonso-Prados, José L; Sandín-España, Pilar

2017-11-01

The scientific community and regulatory bodies worldwide, currently promote the development of non-experimental tests that produce reliable data for pesticide risk assessment. The use of standard quantum chemistry methods could allow the development of tools to perform a first screening of compounds to be considered for the experimental studies, improving the risk assessment. This fact results in a better distribution of resources and in better planning, allowing a more exhaustive study of the pesticides and their metabolic products. The current paper explores the potential of quantum chemistry in modelling toxicity and environmental behaviour of pesticides and their by-products by using electronic descriptors obtained computationally. Quantum chemistry has potential to estimate the physico-chemical properties of pesticides, including certain chemical reaction mechanisms and their degradation pathways, allowing modelling of the environmental behaviour of both pesticides and their by-products. In this sense, theoretical methods can contribute to performing a more focused risk assessment of pesticides used in the market, and may lead to higher quality and safer agricultural products. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Major methodological constraints to the assessment of environmental status based on the condition of benthic communities

NASA Astrophysics Data System (ADS)

Medeiros, João Paulo; Pinto, Vanessa; Sá, Erica; Silva, Gilda; Azeda, Carla; Pereira, Tadeu; Quintella, Bernardo; Raposo de Almeida, Pedro; Lino Costa, José; José Costa, Maria; Chainho, Paula

2014-05-01

The Marine Strategy Framework Directive (MSFD) was published in 2008 and requires Member States to take the necessary measures to achieve or maintain good environmental status in aquatic ecosystems by the year of 2020. The MSFD indicates 11 qualitative descriptors for environmental status assessment, including seafloor integrity, using the condition of the benthic community as an assessment indicator. Member States will have to define monitoring programs for each of the MSFD descriptors based on those indicators in order to understand which areas are in a Good Environmental Status and what measures need to be implemented to improve the status of areas that fail to achieve that major objective. Coastal and offshore marine waters are not frequently monitored in Portugal and assessment tools have only been developed very recently with the implementation of the Water Framework Directive (WFD). The lack of historical data and knowledge on the constraints of benthic indicators in coastal areas requires the development of specific studies addressing this issue. The major objective of the current study was to develop and test and experimental design to assess impacts of offshore projects. The experimental design consisted on the seasonal and interannual assessment of benthic invertebrate communities in the area of future implementation of the structures (impact) and two potential control areas 2 km from the impact area. Seasonal benthic samples were collected at nine random locations within the impact and control areas in two consecutive years. Metrics included in the Portuguese benthic assessment tool (P-BAT) were calculated since this multimetric tool was proposed for the assessment of the ecological status in Portuguese coastal areas under the WFD. Results indicated a high taxonomic richness in this coastal area and no significant differences were found between impact and control areas, indicating the feasibility of establishing adequate control areas in marine ecosystems. Nevertheless, significant differences were found between different seasons and different years, showing that the coastal benthic communities important temporal variations. Although those variations did not affect the status assessment based on metrics that considered the ratio between sensitive and tolerant taxa, diversity indices showed different classifications between seasons and years. These results indicate the need for a temporal stratification of the monitoring programs. That might be achieved by setting different thresholds for specific seasons or selecting specific monitoring seasons. It might also require a regular assessment of the environmental conditions that support the identification of outlier years, which monitoring results should be carefully considered.

Clinical descriptors for the recognition of central sensitization pain in patients with knee osteoarthritis.

PubMed

Lluch, Enrique; Nijs, Jo; Courtney, Carol A; Rebbeck, Trudy; Wylde, Vikki; Baert, Isabel; Wideman, Timothy H; Howells, Nick; Skou, Søren T

2017-08-02

Despite growing awareness of the contribution of central pain mechanisms to knee osteoarthritis pain in a subgroup of patients, routine evaluation of central sensitization is yet to be incorporated into clinical practice. The objective of this perspective is to design a set of clinical descriptors for the recognition of central sensitization in patients with knee osteoarthritis that can be implemented in clinical practice. A narrative review of original research papers was conducted by nine clinicians and researchers from seven different countries to reach agreement on clinically relevant descriptors. It is proposed that identification of a dominance of central sensitization pain is based on descriptors derived from the subjective assessment and the physical examination. In the former, clinicians are recommended to inquire about intensity and duration of pain and its association with structural joint changes, pain distribution, behavior of knee pain, presence of neuropathic-like or centrally mediated symptoms and responsiveness to previous treatment. The latter includes assessment of response to clinical test, mechanical hyperalgesia and allodynia, thermal hyperalgesia, hypoesthesia and reduced vibration sense. This article describes a set of clinically relevant descriptors that might indicate the presence of central sensitization in patients with knee osteoarthritis in clinical practice. Although based on research data, the descriptors proposed in this review require experimental testing in future studies. Implications for Rehabilitation Laboratory evaluation of central sensitization for people with knee osteoarthritis is yet to be incorporated into clinical practice. A set of clinical indicators for the recognition of central sensitization in patients with knee osteoarthritis is proposed. Although based on research data, the clinical indicators proposed require further experimental testing of psychometric properties.

Self-organizing maps of molecular descriptors for sesquiterpene lactones and their application to the chemotaxonomy of the Asteraceae family.

PubMed

Scotti, Marcus T; Emerenciano, Vicente; Ferreira, Marcelo J P; Scotti, Luciana; Stefani, Ricardo; da Silva, Marcelo S; Mendonça Junior, Francisco Jaime B

2012-04-20

The Asteraceae, one of the largest families among angiosperms, is chemically characterised by the production of sesquiterpene lactones (SLs). A total of 1,111 SLs, which were extracted from 658 species, 161 genera, 63 subtribes and 15 tribes of Asteraceae, were represented and registered in two dimensions in the SISTEMATX, an in-house software system, and were associated with their botanical sources. The respective 11 block of descriptors: Constitutional, Functional groups, BCUT, Atom-centred, 2D autocorrelations, Topological, Geometrical, RDF, 3D-MoRSE, GETAWAY and WHIM were used as input data to separate the botanical occurrences through self-organising maps. Maps that were generated with each descriptor divided the Asteraceae tribes, with total index values between 66.7% and 83.6%. The analysis of the results shows evident similarities among the Heliantheae, Helenieae and Eupatorieae tribes as well as between the Anthemideae and Inuleae tribes. Those observations are in agreement with systematic classifications that were proposed by Bremer, which use mainly morphological and molecular data, therefore chemical markers partially corroborate with these classifications. The results demonstrate that the atom-centred and RDF descriptors can be used as a tool for taxonomic classification in low hierarchical levels, such as tribes. Descriptors obtained through fragments or by the two-dimensional representation of the SL structures were sufficient to obtain significant results, and better results were not achieved by using descriptors derived from three-dimensional representations of SLs. Such models based on physico-chemical properties can project new design SLs, similar structures from literature or even unreported structures in two-dimensional chemical space. Therefore, the generated SOMs can predict the most probable tribe where a biologically active molecule can be found according Bremer classification.

Contextual modulation of biases in face recognition.

PubMed

Felisberti, Fatima Maria; Pavey, Louisa

2010-09-23

The ability to recognize the faces of potential cooperators and cheaters is fundamental to social exchanges, given that cooperation for mutual benefit is expected. Studies addressing biases in face recognition have so far proved inconclusive, with reports of biases towards faces of cheaters, biases towards faces of cooperators, or no biases at all. This study attempts to uncover possible causes underlying such discrepancies. Four experiments were designed to investigate biases in face recognition during social exchanges when behavioral descriptors (prosocial, antisocial or neutral) embedded in different scenarios were tagged to faces during memorization. Face recognition, measured as accuracy and response latency, was tested with modified yes-no, forced-choice and recall tasks (N = 174). An enhanced recognition of faces tagged with prosocial descriptors was observed when the encoding scenario involved financial transactions and the rules of the social contract were not explicit (experiments 1 and 2). Such bias was eliminated or attenuated by making participants explicitly aware of "cooperative", "cheating" and "neutral/indifferent" behaviors via a pre-test questionnaire and then adding such tags to behavioral descriptors (experiment 3). Further, in a social judgment scenario with descriptors of salient moral behaviors, recognition of antisocial and prosocial faces was similar, but significantly better than neutral faces (experiment 4). The results highlight the relevance of descriptors and scenarios of social exchange in face recognition, when the frequency of prosocial and antisocial individuals in a group is similar. Recognition biases towards prosocial faces emerged when descriptors did not state the rules of a social contract or the moral status of a behavior, and they point to the existence of broad and flexible cognitive abilities finely tuned to minor changes in social context.

Has the tobacco industry evaded the FDA's ban on ‘Light’ cigarette descriptors?

PubMed Central

Connolly, Gregory N; Alpert, Hillel R

2014-01-01

Background Under the Family Smoking Prevention and Tobacco Control Act (FSPTCA), the Food and Drug Administration (FDA) banned the use of “Lights” descriptors or similar terms on tobacco products that convey messages of reduced risk. Manufacturers eliminated terms explicitly stated and substituted colour name descriptors corresponding to the banned terms. This paper examines whether the tobacco industry complied with or circumvented the law and potential FDA regulatory actions. Methods Philip Morris retailer manuals, manufacturers' annual reports filed with the Massachusetts Department of Public Health, a national public opinion survey, and market-wide cigarette sales data were examined. Results Manufacturers substituted “Gold” for “Light” and “Silver” for “Ultra-light” in the names of Marlboro sub-brands, and “Blue”, “Gold”, and “Silver” for banned descriptors in sub-brand names. Percent filter ventilation levels, used to generate the smoke yield ranges associated with “Lights” categories, appear to have been reassigned to the new colour brand name descriptors. Following the ban, 92% of smokers reported they could easily identify their usual brands, and 68% correctly named the package colour associated with their usual brand, while sales for “Lights” cigarettes remained unchanged. Conclusions Tobacco manufacturers appear to have evaded a critical element of the FSPTCA, the ban on misleading descriptors that convey reduced health risk messages. The FPSTCA provides regulatory mechanisms, including banning these products as adulterated (Section 902). Manufacturers could then apply for pre-market approval as new products and produce evidence for FDA evaluation and determination whether or not sales of these products are in the public health interest. PMID:23485704

Multi-texture local ternary pattern for face recognition

NASA Astrophysics Data System (ADS)

Essa, Almabrok; Asari, Vijayan

2017-05-01

In imagery and pattern analysis domain a variety of descriptors have been proposed and employed for different computer vision applications like face detection and recognition. Many of them are affected under different conditions during the image acquisition process such as variations in illumination and presence of noise, because they totally rely on the image intensity values to encode the image information. To overcome these problems, a novel technique named Multi-Texture Local Ternary Pattern (MTLTP) is proposed in this paper. MTLTP combines the edges and corners based on the local ternary pattern strategy to extract the local texture features of the input image. Then returns a spatial histogram feature vector which is the descriptor for each image that we use to recognize a human being. Experimental results using a k-nearest neighbors classifier (k-NN) on two publicly available datasets justify our algorithm for efficient face recognition in the presence of extreme variations of illumination/lighting environments and slight variation of pose conditions.

Universal Fragment Descriptors for Predicting Electronic and Mechanical Properties of Inorganic Crystals

NASA Astrophysics Data System (ADS)

Oses, Corey; Isayev, Olexandr; Toher, Cormac; Curtarolo, Stefano; Tropsha, Alexander

Historically, materials discovery is driven by a laborious trial-and-error process. The growth of materials databases and emerging informatics approaches finally offer the opportunity to transform this practice into data- and knowledge-driven rational design-accelerating discovery of novel materials exhibiting desired properties. By using data from the AFLOW repository for high-throughput, ab-initio calculations, we have generated Quantitative Materials Structure-Property Relationship (QMSPR) models to predict critical materials properties, including the metal/insulator classification, band gap energy, and bulk modulus. The prediction accuracy obtained with these QMSPR models approaches training data for virtually any stoichiometric inorganic crystalline material. We attribute the success and universality of these models to the construction of new materials descriptors-referred to as the universal Property-Labeled Material Fragments (PLMF). This representation affords straightforward model interpretation in terms of simple heuristic design rules that could guide rational materials design. This proof-of-concept study demonstrates the power of materials informatics to dramatically accelerate the search for new materials.

On the Preferred Active Sites of Promoted MoS 2 for Hydrodesulfurization with Minimal Organonitrogen Inhibition

DOE PAGES

Rangarajan, Srinivas; Mavrikakis, Manos

2016-12-14

Hydrodesulfurization is a process to produce ultralow-sulfur diesel fuel. Although promoted molybdenum sulfide (MoS 2) catalysts have been used industrially for several decades, the active site requirements for selective hydrodesulfurization of organosulfur compounds with minimal inhibition by organonitrogen constituents of a real gasoil feed has not been resolved. By using molecular binding energy descriptors derived from plane wave density functional theory calculations for comparative adsorption of organosulfur and organonitrogen compounds, we analyzed more than 20 potential sites on unpromoted and Ni- and Co-promoted MoS 2. We also found that hydrogen sulfide and ammonia are simple descriptors of adsorption of stericallymore » unhindered organosulfur and organonitrogen compounds such as dibenzothiophene and acridine, respectively. Further, organonitrogen compounds in gasoil bind more strongly than organosulfur compounds on all sites except on sites with exposed metal atoms on the corner and sulfur edges of promoted MoS 2. Consequently, these sites are proposed as required for maximum-hydrodesulfurization minimum-inhibition catalysis.« less

Using multi-terminology indexing for the assignment of MeSH descriptors to health resources in a French online catalogue

PubMed Central

Pereira, Suzanne; Névéol, Aurélie; Kerdelhué, Gaétan; Serrot, Elisabeth; Joubert, Michel; Darmoni, Stéfan J.

2008-01-01

Background: To assist with the development of a French online quality-controlled health gateway (CISMeF), an automatic indexing tool assigning MeSH descriptors to medical text in French was created. The French Multi-Terminology Indexer (F-MTI) relies on a multi-terminology approach involving four prominent medical terminologies and the mappings between them. Objective: In this paper, we compare lemmatization and stemming as methods to process French medical text for indexing. We also evaluate the multi-terminology approach implemented in F-MTI. Methods: The indexing strategies were assessed on a corpus of 18,814 resources indexed manually. Results: There is little difference in the indexing performance when lemmatization or stemming is used. However, the multi-terminology approach outperforms indexing relying on a single terminology in terms of recall. Conclusion: F-MTI will soon be used in the CISMeF production environment and in a Health MultiTerminology Server in French. PMID:18998933

Prediction of Partition Coefficients of Organic Compounds between SPME/PDMS and Aqueous Solution

PubMed Central

Chao, Keh-Ping; Lu, Yu-Ting; Yang, Hsiu-Wen

2014-01-01

Polydimethylsiloxane (PDMS) is commonly used as the coated polymer in the solid phase microextraction (SPME) technique. In this study, the partition coefficients of organic compounds between SPME/PDMS and the aqueous solution were compiled from the literature sources. The correlation analysis for partition coefficients was conducted to interpret the effect of their physicochemical properties and descriptors on the partitioning process. The PDMS-water partition coefficients were significantly correlated to the polarizability of organic compounds (r = 0.977, p < 0.05). An empirical model, consisting of the polarizability, the molecular connectivity index, and an indicator variable, was developed to appropriately predict the partition coefficients of 61 organic compounds for the training set. The predictive ability of the empirical model was demonstrated by using it on a test set of 26 chemicals not included in the training set. The empirical model, applying the straightforward calculated molecular descriptors, for estimating the PDMS-water partition coefficient will contribute to the practical applications of the SPME technique. PMID:24534804

Bibliography on Liquefied Natural Gas (LNG) safety

NASA Technical Reports Server (NTRS)

Ordin, P. M.

1976-01-01

Approximately 600 citations concerning safety of liquefied natural gas and liquid methane are presented. Each entry includes the title, author, abstract, source, description of figures, key references, and major descriptors for retrieving the document. An author index is provided as well as an index of descriptors.

Fruit morphological descriptors as a tool for discrimination of Daucus L. germplasm

USDA-ARS?s Scientific Manuscript database

Morphological diversity of a Daucus L. germplasm collection maintained at the National Gene Bank of Tunisia was assessed using fourteen morphological descriptors related to mature fruits. Quantification of variability for each character was investigated using the standardized Shannon-Weaver Diversit...

Usefulness of descriptors in phenotyping germplasm collections

USDA-ARS?s Scientific Manuscript database

A large number of crop germplasm collections are maintained within the U.S. National Plant Germplasm System (NPGS). For each of these crop collections, Crop Germplasm committees (CGC), crop curators, and collection staff have established extensive lists of descriptors or phenotypic traits by which t...

Prediction of boiling points of organic compounds by QSPR tools.

PubMed

Dai, Yi-min; Zhu, Zhi-ping; Cao, Zhong; Zhang, Yue-fei; Zeng, Ju-lan; Li, Xun

2013-07-01

The novel electro-negativity topological descriptors of YC, WC were derived from molecular structure by equilibrium electro-negativity of atom and relative bond length of molecule. The quantitative structure-property relationships (QSPR) between descriptors of YC, WC as well as path number parameter P3 and the normal boiling points of 80 alkanes, 65 unsaturated hydrocarbons and 70 alcohols were obtained separately. The high-quality prediction models were evidenced by coefficient of determination (R(2)), the standard error (S), average absolute errors (AAE) and predictive parameters (Qext(2),RCV(2),Rm(2)). According to the regression equations, the influences of the length of carbon backbone, the size, the degree of branching of a molecule and the role of functional groups on the normal boiling point were analyzed. Comparison results with reference models demonstrated that novel topological descriptors based on the equilibrium electro-negativity of atom and the relative bond length were useful molecular descriptors for predicting the normal boiling points of organic compounds. Copyright © 2013 Elsevier Inc. All rights reserved.

A Novel Cylindrical Representation for Characterizing Intrinsic Properties of Protein Sequences.

PubMed

Yu, Jia-Feng; Dou, Xiang-Hua; Wang, Hong-Bo; Sun, Xiao; Zhao, Hui-Ying; Wang, Ji-Hua

2015-06-22

The composition and sequence order of amino acid residues are the two most important characteristics to describe a protein sequence. Graphical representations facilitate visualization of biological sequences and produce biologically useful numerical descriptors. In this paper, we propose a novel cylindrical representation by placing the 20 amino acid residue types in a circle and sequence positions along the z axis. This representation allows visualization of the composition and sequence order of amino acids at the same time. Ten numerical descriptors and one weighted numerical descriptor have been developed to quantitatively describe intrinsic properties of protein sequences on the basis of the cylindrical model. Their applications to similarity/dissimilarity analysis of nine ND5 proteins indicated that these numerical descriptors are more effective than several classical numerical matrices. Thus, the cylindrical representation obtained here provides a new useful tool for visualizing and charactering protein sequences. An online server is available at http://biophy.dzu.edu.cn:8080/CNumD/input.jsp .

Assigning Main Orientation to an EOH Descriptor on Multispectral Images.

PubMed

Li, Yong; Shi, Xiang; Wei, Lijun; Zou, Junwei; Chen, Fang

2015-07-01

This paper proposes an approach to compute an EOH (edge-oriented histogram) descriptor with main orientation. EOH has a better matching ability than SIFT (scale-invariant feature transform) on multispectral images, but does not assign a main orientation to keypoints. Alternatively, it tends to assign the same main orientation to every keypoint, e.g., zero degrees. This limits EOH to matching keypoints between images of translation misalignment only. Observing this limitation, we propose assigning to keypoints the main orientation that is computed with PIIFD (partial intensity invariant feature descriptor). In the proposed method, SIFT keypoints are detected from images as the extrema of difference of Gaussians, and every keypoint is assigned to the main orientation computed with PIIFD. Then, EOH is computed for every keypoint with respect to its main orientation. In addition, an implementation variant is proposed for fast computation of the EOH descriptor. Experimental results show that the proposed approach performs more robustly than the original EOH on image pairs that have a rotation misalignment.

Lagrangian Descriptors: A Method for Revealing Phase Space Structures of General Time Dependent Dynamical Systems

NASA Astrophysics Data System (ADS)

Mancho, Ana M.; Wiggins, Stephen; Curbelo, Jezabel; Mendoza, Carolina

2013-11-01

Lagrangian descriptors are a recent technique which reveals geometrical structures in phase space and which are valid for aperiodically time dependent dynamical systems. We discuss a general methodology for constructing them and we discuss a ``heuristic argument'' that explains why this method is successful. We support this argument by explicit calculations on a benchmark problem. Several other benchmark examples are considered that allow us to assess the performance of Lagrangian descriptors with both finite time Lyapunov exponents (FTLEs) and finite time averages of certain components of the vector field (``time averages''). In all cases Lagrangian descriptors are shown to be both more accurate and computationally efficient than these methods. We thank CESGA for computing facilities. This research was supported by MINECO grants: MTM2011-26696, I-Math C3-0104, ICMAT Severo Ochoa project SEV-2011-0087, and CSIC grant OCEANTECH. SW acknowledges the support of the ONR (Grant No. N00014-01-1-0769).

Sensory shelf life of dulce de leche.

PubMed

Garitta, L; Hough, G; Sánchez, R

2004-06-01

The objectives of this research were to determine the sensory cutoff points for dulce de leche (DL) critical descriptors, both for defective off-flavors and for storage changes in desirable attributes, and to estimate the shelf life of DL as a function of storage temperature. The critical descriptors used to determine the cutoff points were plastic flavor, burnt flavor, dark color, and spreadability. Linear correlations between sensory acceptability and trained panel scores were used to determine the sensory failure cutoff point for each descriptor. To estimate shelf life, DL samples were stored at 25, 37, and 45 degrees C. Plastic flavor was the first descriptor to reach its cutoff point at 25 degrees C and was used for shelf-life calculations. Plastic flavor vs. storage time followed zero-order reaction rate. Shelf-life estimations at different temperatures were 109 d at 25 degrees C, 53 d at 37 degrees C, and 9 d at 45 degrees C. The activation energy, necessary to calculate shelf lives at different temperatures, was 14,370 +/- 2080 cal/mol.