1,620 research outputs found
Lowest electronic states of neutral and ionic LiN
No full textWe have investigated the potential energy curves (PECs) of the LiN heteronuclear diatomic molecule, including its ionic species LiN+ and LiN−, using explicitly correlated multi-reference configuration interaction (MRCI-F12) calculations in conjunction with the correlation consistent quintuple- basis set. The effect of core–valence correlation, scalar relativistic effects, and the size of the basis sets has been investigated. A comprehensive set of spectroscopic constants determined based on the above-mentioned calculations are also reported for the lowest electronic states and all systems, including dissociation energies, harmonic and anharmonic vibrational frequencies, and rotational constants. Additional parameters, such as the dipole moments, equilibrium spin-orbit constants, excitation energies, and rovibrational energy levels, are also documented. We found that the three triplet states of LiN, namely, X 3∑−, A 3Π, and 2 3∑−, exhibit substantial potential wells in the PEC diagrams, while the quintet states are repulsive in nature. The ground state of the anion also shows a deep potential well in the vicinity of its equilibrium geometry. In contrast, the ground and excited states of the cation are very loosely bound. Charge transfer properties of each of these states are also analyzed to obtain an in-depth understanding of the interatomic interactions. We found that the core–valence correlation has a substantial effect on the calculated spectroscopic constants.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Atmospheric Remote Sensin
Ariel - Volume 2 Number 3
No full textEditors
Delvyn C. Case, Jr.
Paul M. Fernhoff
News Editors
Richard Bonanno
Daniel B. Gould
Robin A. Edwards
Lay-Out Editor
Carol Dolinskas
Sports Editor
James J. Nocon
Contributing Editors
Michael J. Blecker
Lin Sey Edwards
Jack Guralnik
W. Cherry Light
Features Editor
Steven A. Ager
Donald A. Bergman
Stephen P. Flynn
Business Manager
Nick Greg
Restricted Four-Valued Semantics for Answer Set Programming
No full textIn answer set programming, an extended logic program may have no answer set, or only one trivial answer set. In this paper, we propose a new stable model semantics based on the restricted four-valued logic to overcome both inconsistences and incoherences in answer set programming. Our stable models coincide with classical answer sets when reasoning on consistent and coherent logic programs, and can be solved by transformation in existing ASP solvers. We also show the connection between our stable models and the extensions of default logic.EICPCI-S(ISTP)[email protected]; [email protected]
PAN14 Author Identification: Verification
No full textWe provide you with a training corpus that comprises a set of author verification problems in several languages/genres. Each problem consists of some (up to five) known documents by a single person and exactly one questioned document. All documents within a single problem instance will be in the same language and best efforts are applied to assure that within-problem documents are matched for genre, register, theme, and date of writing. The document lengths vary from a few hundred to a few thousand words.
More information: Lin
PAN18 Author Identification: Attribution
No full textWe provide a corpus which comprises a set of cross-domain authorship attribution problems in each of the following 5 languages: English, French, Italian, Polish, and Spanish. Note that we specifically avoid to use the term 'training corpus' because the sets of candidate authors of the development and the evaluation corpora are not overlapping. Therefore, your approach should not be designed to particularly handle the candidate authors of the development corpus.
Each problem consists of a set of known fanfics by each candidate author and a set of unknown fanfics located in separate folders. The file problem-info.json that can be found in the main folder of each problem, shows the name of folder of unknown documents and the list of names of candidate author folders.
The true author of each unknown document can be seen in the file ground-truth.json, also found in the main folder of each problem.
In addition, to handle a collection of such problems, the file collection-info.jsonincludes all relevant information. In more detail, for each problem it lists its main folder, the language (either "en", "fr", "it", "pl", or "sp") and encoding (always UTF-8) of its documents.
More information: Lin
Plant acclimation and adaptation to a high CO2 world
No full textPlant adaptation to elevated atmospheric carbon dioxide (CO2) is of great interest, as the concentration of this gas in the atmosphere has risen by more than 30% to 388 µmol mol-1 since the industrial revolution. On average there has been a rise of 3 ppm per year. Plant fossil samples suggest that atmospheric CO2 may be acting as a selective agent driving evolution, but limited evidence is available to support this idea that plants subjected to future predicted concentrations of carbon dioxide may adapt. In contrast, much evidence is available on plant acclimation mechanisms and phenotypinc plasticity in future high CO2 concentrations. Studying evolutionary responses to this aspect of environmental change is difficult, but here we use a CO2 spring site where plants have been exposed for multiple generations to concentrations of CO2 predicted for 2050. From this, detailed phenotyping data were collected, including data for stomatal patterning, photosynthetic performance and growth. Considerable evidence exists to show that stomatal numbers have declined across geological time and that this is linked to CO2 concentration, but few CO2-sensitive stomatal patterning genes have ever been identified. When grown under elevated CO2 concentrations P. lanceolata (the narrow leaf plantain), seeds collected from the spring site showed a counter-intuitive increase in stomatal index and density. Here, in this non-model plant we have investigated the gene expression changes underlying this stomatal patterning response to elevated CO2.RNA-Seq allowed for in-depth analysis in P. lanceolata with no previous information required, enabling rapid evaluation of any of novel plant acclimation and adaption mechanisms. Using this approach we have identified a set of novel genes for stomatal patterning in high CO2 and confirmed previously observed acclimation responses
Visualization for the Coherent Set of 3D Property Units
No full textThere are many 3D objects with denser aggregation that they are fully/partly coherent touched with each other through shared facets, which we called coherent set of 3D objects. Visualization for 3D property unit is an effective way to understand 3D spatial occupation, location and relationship in urban space, particularly in the coherent set of 3D property units. We present a novel method to visualize coherent set of 3D property units with application in 3D cadastre. We innovatively utilise deforming or distorting technique to visualize them, taking account of both the focused 3D objects and the coherent set. This visualization approach can illustrate not only the relative locations, spatial relationships of/between them, but also the highlighted shape, location of the focused/selected 3D object. Also we try to display spatial relationship explicitly between 3D objects to preserve our spatial cognition about the spatial layout and distribution
Combination of Feature Engineering and Ranking Models for Paper-Author Identification in KDD Cup 2013 Hsiao-Yu Tung Hsuan-Tien Lin
No full textAbstract This paper describes the winning solution of team National Taiwan University for track 1 of KDD Cup 2013. The track 1 in KDD Cup 2013 considers the paper-author identification problem, which is to identify whether a paper is truly written by an author. First, we conduct feature engineering to transform the various types of provided text information into 97 features. Second, we train classification and ranking models using these features. Last, we combine our individual models to boost the performance by using results on the internal validation set and the official Valid set. Some effective post-processing techniques have also been proposed. Our solution achieves 0.98259 MAP score and ranks the first place on the private leaderboard of the Test set
PAN17 Author Profiling
No full textWe provide you with a training data set that consists of Twitter tweets in English, Spanish, Portuguese and Arabic, labeled with gender and language variety.
More information about the task: Lin
Fast identification of biological pathways associated with a quantitative trait using group lasso with overlaps.
No full textWhere causal SNPs (single nucleotide polymorphisms) tend to accumulate within biological pathways, the incorporation of prior pathways information into a statistical model is expected to increase the power to detect true associations in a genetic association study. Most existing pathways-based methods rely on marginal SNP statistics and do not fully exploit the dependence patterns among SNPs within pathways.We use a sparse regression model, with SNPs grouped into pathways, to identify causal pathways associated with a quantitative trait. Notable features of our "pathways group lasso with adaptive weights" (P-GLAW) algorithm include the incorporation of all pathways in a single regression model, an adaptive pathway weighting procedure that accounts for factors biasing pathway selection, and the use of a bootstrap sampling procedure for the ranking of important pathways. P-GLAW takes account of the presence of overlapping pathways and uses a novel combination of techniques to optimise model estimation, making it fast to run, even on whole genome datasets.In a comparison study with an alternative pathways method based on univariate SNP statistics, our method demonstrates high sensitivity and specificity for the detection of important pathways, showing the greatest relative gains in performance where marginal SNP effect sizes are small
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