3,064 research outputs found
The Scaled-Charge Additive Force Field for Amino Acid Based Ionic Liquids
Abstract. Ionic liquids (ILs) constitute an emerging field of research. New
ILs are continuously introduced involving more and more organic and inorganic
ions. Amino acid based ILs (AAILs) represent a specific interest due to their
evolutional connection to proteins. We report a new non- polarizable force
field (FF) for the eight AAILs comprising 1-ethyl-3-methylimidazolium cation
and amino acid anions. The anions were obtained via deprotonation of carboxyl
group. Specific cation-anion non-covalent interactions have been taken into
account by computing electrostatic potential for ion pairs, in contrast to
isolated ions. The van der Waals interactions have been transferred from the
CHARMM36 FF with minor modifications. Therefore, compatibility between our
parameters and CHARMM36 parameters is preserved. Our FF can be easily
implemented using a variety of popular molecular dynamics programs. It will
find broad applications in computational investigation of ILs
ACME vs PDDL: support for dynamic reconfiguration of software architectures
On the one hand, ACME is a language designed in the late 90s as an
interchange format for software architectures. The need for recon guration at
runtime has led to extend the language with speci c support in Plastik. On the
other hand, PDDL is a predicative language for the description of planning
problems. It has been designed in the AI community for the International
Planning Competition of the ICAPS conferences. Several related works have
already proposed to encode software architectures into PDDL. Existing planning
algorithms can then be used in order to generate automatically a plan that
updates an architecture to another one, i.e., the program of a recon guration.
In this paper, we improve the encoding in PDDL. Noticeably we propose how to
encode ADL types and constraints in the PDDL representation. That way, we can
statically check our design and express PDDL constraints in order to ensure
that the generated plan never goes through any bad or inconsistent
architecture, not even temporarily.Comment: 6\`eme \'edition de la Conf\'erence Francophone sur les Architectures
Logicielles (CAL 2012), Montpellier : France (2012
Exploding Nitromethane in silico, in real time
Nitromethane (NM) is widely applied in chemical technology as a solvent for
extraction, cleaning and chemical synthesis. NM was considered safe for a long
time, until a railroad tanker car exploded in 1958. We investigate detonation
kinetics and reaction mechanisms in a variety of systems consisting of NM,
molecular oxygen and water vapor. State-of-the-art reactive molecular dynamics
allows us to simulate reactions in time-domain, as they occur in real life.
High polarity of the NM molecule is shown to play an important role, driving
the first exothermic step of the reaction. Presence of oxygen is important for
faster oxidation, whereas its optimal concentration is in agreement with the
proposed reaction mechanism. Addition of water (50 mol%) inhibits detonation;
however, water does not prevent detonation entirely. The reported results
provide important insights for improving applications of NM and preserving
safety of industrial processes.Comment: arXiv admin note: text overlap with arXiv:1408.372
Cross-validation and Peeling Strategies for Survival Bump Hunting using Recursive Peeling Methods
We introduce a framework to build a survival/risk bump hunting model with a
censored time-to-event response. Our Survival Bump Hunting (SBH) method is
based on a recursive peeling procedure that uses a specific survival peeling
criterion derived from non/semi-parametric statistics such as the
hazards-ratio, the log-rank test or the Nelson-Aalen estimator. To optimize the
tuning parameter of the model and validate it, we introduce an objective
function based on survival or prediction-error statistics, such as the log-rank
test and the concordance error rate. We also describe two alternative
cross-validation techniques adapted to the joint task of decision-rule making
by recursive peeling and survival estimation. Numerical analyses show the
importance of replicated cross-validation and the differences between criteria
and techniques in both low and high-dimensional settings. Although several
non-parametric survival models exist, none addresses the problem of directly
identifying local extrema. We show how SBH efficiently estimates extreme
survival/risk subgroups unlike other models. This provides an insight into the
behavior of commonly used models and suggests alternatives to be adopted in
practice. Finally, our SBH framework was applied to a clinical dataset. In it,
we identified subsets of patients characterized by clinical and demographic
covariates with a distinct extreme survival outcome, for which tailored medical
interventions could be made. An R package `PRIMsrc` is available on CRAN and
GitHub.Comment: Keywords: Exploratory Survival/Risk Analysis, Survival/Risk
Estimation & Prediction, Non-Parametric Method, Cross-Validation, Bump
Hunting, Rule-Induction Metho
- …