Dibenzoylhydrazines as Insect Growth Modulators: Topology-Based QSAR Modelling

Dibenzoylhydrazines Xa-(C6H5)a-CO-N-(t-Bu)-NH-CO-(C6H5)b-Yb are efficient insect growth regulators with high activity and selectivity toward lepidopteran and coleopteran pests. For 123 congeneric molecules, a quantitative structure activity relationship model was built in the framework of the QSARINS package using 2D, Topology-based, PaDEL descriptors. Variable selection by GA-MLR allows building an efficient multilinear regression linking pEC50 values to nine structural variables. Robustness and quality of the model were carefully examined at various levels: data-fitting (recall), leave-one (or some) - out, internal and external validation (including random splitting), points not in depth investigated in previous works. Various Machine Learning approaches (Partial Least Squares Regression, Projection Pursuit Regression, Linear Support Vector Machine or Three Layer Perceptron Artificial Neural Network) confirm the validity of the analysis, giving highly consistent results of comparable quality, with only a slight advantage for the three-layer perceptron

Computation of free energy profiles with parallel adaptive dynamics

We propose a formulation of adaptive computation of free energy differences, in the ABF or nonequilibrium metadynamics spirit, using conditional distributions of samples of configurations which evolve in time. This allows to present a truly unifying framework for these methods, and to prove convergence results for certain classes of algorithms. From a numerical viewpoint, a parallel implementation of these methods is very natural, the replicas interacting through the reconstructed free energy. We show how to improve this parallel implementation by resorting to some selection mechanism on the replicas. This is illustrated by computations on a model system of conformational changes.Comment: 4 pages, 1 Figur

A Backward Particle Interpretation of Feynman-Kac Formulae

We design a particle interpretation of Feynman-Kac measures on path spaces based on a backward Markovian representation combined with a traditional mean field particle interpretation of the flow of their final time marginals. In contrast to traditional genealogical tree based models, these new particle algorithms can be used to compute normalized additive functionals "on-the-fly" as well as their limiting occupation measures with a given precision degree that does not depend on the final time horizon. We provide uniform convergence results w.r.t. the time horizon parameter as well as functional central limit theorems and exponential concentration estimates. We also illustrate these results in the context of computational physics and imaginary time Schroedinger type partial differential equations, with a special interest in the numerical approximation of the invariant measure associated to $h$-processes

Reweighting for Nonequilibrium Markov Processes Using Sequential Importance Sampling Methods

We present a generic reweighting method for nonequilibrium Markov processes. With nonequilibrium Monte Carlo simulations at a single temperature, one calculates the time evolution of physical quantities at different temperatures, which greatly saves the computational time. Using the dynamical finite-size scaling analysis for the nonequilibrium relaxation, one can study the dynamical properties of phase transitions together with the equilibrium ones. We demonstrate the procedure for the Ising model with the Metropolis algorithm, but the present formalism is general and can be applied to a variety of systems as well as with different Monte Carlo update schemes.Comment: accepted for publication in Phys. Rev. E (Rapid Communications

Particle filtering for joint symbol and code delay estimation in DS spread spectrum systems in multipath environment

We develop a new receiver for joint symbol, channel characteristics, and code delay estimation for DS spread spectrum systems under conditions of multipath fading. The approach is based on particle filtering techniques and combines sequential importance sampling, a selection scheme, and a variance reduction technique. Several algorithms involving both deterministic and randomized schemes are considered and an extensive simulation study is carried out in order to demonstrate the performance of the proposed methods.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Macroeconomic trends and practice models impacting acute care surgery

Acute care surgery (ACS) diagnoses are responsible for approximately a quarter of the costs of inpatient care in the US government, and individuals will be responsible for a larger share of the costs of this healthcare as the population ages. ACS as a specialty thus has the opportunity to meet a significant healthcare need, and by optimizing care delivery models do so in a way that improves both quality and value. ACS practice models that have maintained or added emergency general surgery (EGS) and even elective surgery have realized more operative case volume and surgeon satisfaction. However, vulnerabilities exist in the ACS model. Payer mix in a practice varies by geography and distribution of EGS, trauma, critical care, and elective surgery. Critical care codes constitute approximately 25% of all billing by acute care surgeons, so even small changes in reimbursement in critical care can have significant impact on professional revenue. Staffing an ACS practice can be challenging depending on reimbursement and due to uneven geographic distribution of available surgeons. Empowered by an understanding of economics, using team-oriented leadership inherent to trauma surgeons, and in partnership with healthcare organizations and regulatory bodies, ACS surgeons are positioned to significantly influence the future of healthcare in the USA

An original interferometric study of NGC 1068 with VISIR BURST mode images

We present 12.8 microns images of the core of NGC 1068 obtained with the BURST mode of the VLT/VISIR. We trace structures under the diffraction limit of one UT and we investigate the link between dust in the vicinity of the central engine of NGC 1068, recently resolved by interferometry with MIDI, and more extended structures. This step is mandatory for a multi-scale understanding of the sources of mid-infrared emission in AGNs. A speckle processing of VISIR BURST mode images was performed to extract very low spatial-frequency visibilities, first considering the full field of VISIR BURST mode images and then limiting it to the mask used for the acquisition of MIDI data. Extracted visibilities are reproduced with a multi-component model. We identify two major sources of emission: one compact < 85 mas, associated with the dusty torus, and an elliptical one, (< 140) mas x 1187 mas at P.A.=-4 degrees from N to E. This is consistent with previous deconvolution processes. The combination with MIDI data reveals the close environment of the dusty torus to contribute to about 83 percent of the MIR flux seen by MIDI. This strong contribution has to be considered in modeling long baseline interferometric data. It must be related to the NS elongated component which is thought to originate from individually unresolved dusty clouds and is located inside the ionization cone. Low temperatures of the dusty torus are not challenged, emphasizing the scenarios of clumpy torus.Comment: 10 pages, 7 figures, accepted for publication in A&