1,720,980 research outputs found
Exploring the QSARs for OH Tropospheric Degradation of VOCs using freely available online descriptors
No full textTropospheric photochemical air pollution has impacts on scales ranging from local to global. The reactions of organic pollutants in the atmosphere with OH radicals, NO3 radicals, and ozone are of great concern from an ecological standpoint for risk assessment measurement such as degradation pathways, atmospheric lifetimes and fate of these compounds. It was already established that reactions with hydroxyl radical (-OH) is the most important pathway of day time removal of organic pollutant in atmosphere because of the reactive nature of OH radical to react practically almost with every volatile organic compounds (VOCs) in the troposphere. Due to limited availability of experimental gas phase rate constant data for chemicals, alternative theoretical approaches like QSAR/QSPRs are often practiced to predict the high risk of organic chemicals and to reduce the time consuming, expensive and difficult experimental procedures.
In this study we developed QSAR models for hydroxyl radical tropospheric degradation rate of 460 VOCs, using HOMO, LUMO from Hyperchem minimization in addition to separately freely available online molecular descriptors (from the CADASTER online platform– www.cadaster.eu) or descriptors calculated from an updated version of DRAGON software. The Genetic Algorithm as Variable Subset Selection (GA-VSS) was used to select the relevant molecular descriptors in the modeling step (Ordinary Least Squares (OLS) regression). Three splitting criteria [K-ANN, k-means cluster and random on response] were applied for verifying the external predictivity of developed QSAR models, with special emphasis on model applicability domain which was verified by the leverage approach. The statistical qualities of the models developed from the pool of online descriptors were comparable with those obtained from the DRAGON descriptors and, most importantly, the GA selected, in addition to HOMO, descriptors with comparable mechanistic meaning, from completely different pool of input descriptors.
So it can be suggested to use online freely available descriptors to increase the reproducibility of the models for the safety of environment and for REACH
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Hydroxyl radical reaction rate constant model
No full textTropospheric photochemical air pollution has impacts on scales ranging from local to global. Reactions with hydroxyl radical (OH.) is the most important pathway of day time removal of organic pollutants in atmosphere. Theoretical approaches as QSAR/QSPRs are often used to predict the high risk of organic chemicals to reduce the time consuming, expensive and difficult experimental procedures. The crucial importance of the three central OECD principles for QSAR model validation is highlighted in a case study of tropospheric degradation of volatile organic pollutants (VOCs) by OH, applied to two CADASTER chemical classes (PBDEs and (benzo)triazoles). The application of any QSAR model to chemicals without experimental data largely depends on model reproducibility by the user. The reproducibility of an unambiguous algorithm (OECD Principle 2) is guaranteed by redeveloping MLR models based on updated version of DRAGON software for molecular descriptors calculation and some freely available online descriptors. The Genetic Algorithm has confirmed its ability to select similarly informative descriptors, independently on the input pool of variables. The ability of the GA-selected descriptors to predict chemicals, not used in model development, is verified by three different splittings (random by response, K-ANN and K-means clustering by structural similarity), thus ensuring the external predictivity of the new models (OECD Principle 4), independently of the training/prediction set composition, as verified by various validation parameters. The relevance of checking the structural applicability domain (OECD Principle 3) becomes evident on comparing the predictions for CADASTER chemicals, using the new models proposed herein, with those obtained by EPI Suite
Aquatic toxicity prediction of diverse pesticides on two algal species using QSTR modeling approach
No full textWith the aim of identification of toxic nature of the diverse pesticides on the aquatic compartment, a large dataset of pesticides (n = 325) with experimental toxicity data on two algal test species (Pseudokirchneriella subcapitata (PS) (synonym: Raphidocelis subcapitata, Selenastrum capricornutum) and Scenedemus subspicatus (SS)) was gathered and subjected to quantitative structure toxicity relationship (QSTR) analysis to predict aquatic toxicity of pesticides. The QSTR models were developed by multiple linear regressions (MLRs), and the genetic algorithm (GA) was used for the variable selection. The developed GA-MLR models were statistically robust enough internally (Q2LOO = 0.620–0.663) and externally (Q2Fn = 0.693–0.868, CCCext = 0.843–0.877). The leverage approach of applicability domain (AD) and prediction reliability indicator assured the reliability of the developed models. The mechanistic interpretation highlighted that the presence of SO2, F and aromatic rings influenced the toxicity of pesticides towards PS species while the presence of alkyl, alkyl halide, aromatic rings and carbonyl was responsible for the toxicity of pesticides towards SS species. Additionally, we have reported the application of developed models to pesticides without experimental value and the cumulative toxicity of pesticides on the aquatic environment by using principal component analysis (PCA). The reliable prediction and prioritization of toxic compounds from the developed models will be useful in the aquatic toxicity assessment of pesticides. Graphical abstract: [Figure not available: see fulltext.
QSAR model reproducibility and applicability: a case study of hydroxyl radical reaction rate constants model
No full textVariations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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