BASBL: Branch-And-Sandwich BiLevel solver. Implementation and computational study with the BASBLib test set

The fate of hexachlorobenzene (HCB) in soil represents a critical environmental problem. Once HCB has reached the soil it will interact with soil constituents, especially soil organic matter (SOM). The understanding of this interaction is important for choosing effective remediation procedures. Here we report a study of binding of HCB to a test set of molecules, which was developed to mimic representative functional groups of SOM. The binding energy of complexes formed by HCB and the test set molecules were investigated at different levels of theory. Effects of different types of dispersion correction to DFT, basis sets and DFT-functionals have been studied. Moreover, the general ability of dispersion-corrected DFT to represent this interaction has been benchmarked against methods such as MP2 and CCSD. As a result the B3LYP-D3 dispersion correction combined with the 6-311++G(2d,2p) basis set was found to be a compromise between accuracy and efficiency and it is recommended for studying this type of non-covalent interaction. Moreover, the performance of the GROMOS force field in the description of this interaction has been tested.

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Computational assessment of the crystallization tendency of 1-ethyl-3-methylimidazolium ionic liquids

Physical Chemistry Chemical Physics ◽

10.1039/d0cp06083f ◽

2021 ◽

Vol 23 (8) ◽

pp. 4951-4962

Author(s):

Ctirad Červinka ◽

Vojtěch Štejfa

Keyword(s):

Ionic Liquids ◽

Computational Study ◽

Test Set ◽

Crystalline Phases ◽

Crystallization Tendency

A test set of 20 1-ethyl-3-methylimidazolium ionic liquids is subjected to a computational study with an aim to interpret the experimental difficulties related to the preparation of crystalline phases of the selected species.

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Computational Study on Joint Visual Attention How with Intentional Agency by Serial Architecture with Goals and Means

PsycEXTRA Dataset ◽

10.1037/e428862008-001 ◽

2008 ◽

Author(s):

Konno Takeshi ◽

Hashimoto Takashi

Keyword(s):

Visual Attention ◽

Computational Study ◽

Joint Visual Attention ◽

Intentional Agency

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Using Connectionist Modules for Decision Support

Methods of Information in Medicine ◽

10.1055/s-0038-1634790 ◽

1990 ◽

Vol 29 (03) ◽

pp. 167-181 ◽

Cited By ~ 6

Author(s):

G. Hripcsak

Keyword(s):

Decision Support ◽

Standard Deviation ◽

Confidence Interval ◽

Posterior Probability ◽

Back Propagation ◽

Connectionist Model ◽

Test Set ◽

The Third ◽

Independent Test ◽

Better Than

AbstractA connectionist model for decision support was constructed out of several back-propagation modules. Manifestations serve as input to the model; they may be real-valued, and the confidence in their measurement may be specified. The model produces as its output the posterior probability of disease. The model was trained on 1,000 cases taken from a simulated underlying population with three conditionally independent manifestations. The first manifestation had a linear relationship between value and posterior probability of disease, the second had a stepped relationship, and the third was normally distributed. An independent test set of 30,000 cases showed that the model was better able to estimate the posterior probability of disease (the standard deviation of residuals was 0.046, with a 95% confidence interval of 0.046-0.047) than a model constructed using logistic regression (with a standard deviation of residuals of 0.062, with a 95% confidence interval of 0.062-0.063). The model fitted the normal and stepped manifestations better than the linear one. It accommodated intermediate levels of confidence well.

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