Electric-field-dependent empirical potentials for molecules and crystals: a first application to flexible water molecule adsorbed in zeolites

A general method to include electric-field-dependent terms in empirical potential functions representing interatomic interactions is proposed. It is applied to derive an intramolecular potential model for the water molecule able to reproduce the effects of an electric field on its geometry and dynamics: to enlarge the HOH angle, to increase slightly the OH bond lengths, to red-shift the stretching vibrational frequencies, and to blue-shift slightly the bending mode frequency. These effects have been detected experimentally for water adsorbed in zeolites and have been confirmed by quantum mechanical calculations. The electric-field-dependent intramolecular potential model for water has been combined with a newly refined intermolecular potential for bulk water and with new potentials representing cation–water and aluminosilicate–water interactions in order to simulate, by classical molecular dynamics (MD) technique, the behavior of water adsorbed in zeolites. The performances of the model have been checked by a MD simulation of liquid water at room temperature, by the structural and vibrational properties of the water dimer, and by test MD calculations on a hydrated natural zeolite (natrolite). The results are encouraging, and the simulations will be extended to study the behavior of water adsorbed in other zeolites, including diffusion and some aspects of ion exchange processes

Exact Solutions to the Sine-Gordon Equation

A systematic method is presented to provide various equivalent solution formulas for exact solutions to the sine-Gordon equation. Such solutions are analytic in the spatial variable $x$ and the temporal variable $t,$ and they are exponentially asymptotic to integer multiples of $2\pi$ as $x\to\pm\infty.$ The solution formulas are expressed explicitly in terms of a real triplet of constant matrices. The method presented is generalizable to other integrable evolution equations where the inverse scattering transform is applied via the use of a Marchenko integral equation. By expressing the kernel of that Marchenko equation as a matrix exponential in terms of the matrix triplet and by exploiting the separability of that kernel, an exact solution formula to the Marchenko equation is derived, yielding various equivalent exact solution formulas for the sine-Gordon equation.Comment: 43 page

A unified approach to Darboux transformations

We analyze a certain class of integral equations related to Marchenko equations and Gel'fand-Levitan equations associated with various systems of ordinary differential operators. When the integral operator is perturbed by a finite-rank perturbation, we explicitly evaluate the change in the solution. We show how this result provides a unified approach to Darboux transformations associated with various systems of ordinary differential operators. We illustrate our theory by deriving the Darboux transformation for the Zakharov-Shabat system and show how the potential and wave function change when a discrete eigenvalue is added to the spectrum.Comment: final version that will appear in Inverse Problem

Flow-based detection and proxy-based evasion of encrypted malware C2 traffic

State of the art deep learning techniques are known to be vulnerable to evasion attacks where an adversarial sample is generated from a malign sample and misclassified as benign. Detection of encrypted malware command and control traffic based on TCP/IP flow features can be framed as a learning task and is thus vulnerable to evasion attacks. However, unlike e.g. in image processing where generated adversarial samples can be directly mapped to images, going from flow features to actual TCP/IP packets requires crafting the sequence of packets, with no established approach for such crafting and a limitation on the set of modifiable features that such crafting allows. In this paper we discuss learning and evasion consequences of the gap between generated and crafted adversarial samples. We exemplify with a deep neural network detector trained on a public C2 traffic dataset, white-box adversarial learning, and a proxy-based approach for crafting longer flows. Our results show 1) the high evasion rate obtained by using generated adversarial samples on the detector can be significantly reduced when using crafted adversarial samples; 2) robustness against adversarial samples by model hardening varies according to the crafting approach and corresponding set of modifiable features that the attack allows for; 3) incrementally training hardened models with adversarial samples can produce a level playing field where no detector is best against all attacks and no attack is best against all detectors, in a given set of attacks and detectors. To the best of our knowledge this is the first time that level playing field feature set- and iteration-hardening are analyzed in encrypted C2 malware traffic detection.Comment: 9 pages, 6 figure

The human major sublingual gland and its neuropeptidergic and nitrergic innervations

Background: What textbooks usually call the sublingual gland in humans is in reality a tissue mass of two types of salivary glands, the anteriorly located consisting of a cluster of minor sublingual glands and the posteriorly located major sublingual gland with its outlet via Bartholin's duct. Only recently, the adrenergic and cholinergic innervations of the major sublingual gland was reported, while information regarding the neuropeptidergic and nitrergic innervations is still lacking. Methods: Bioptic and autoptic specimens of the human major sublingual gland were examined by means of immunohistochemistry for the presence of vasoactive intestinal peptide (VIP)-, neuropeptide Y (NPY)-, substance P (SP)-, calcitonin gene related-peptide (CGRP)-, and neuronal nitric oxide synthase (nNOS)-labeled neuronal structures. Results: As to the neuropeptidergic innervation of secretory cells (here in the form of mucous tubular and seromucous cells), the findings showed many VIP-containing nerves, few NPY- and SP-containing nerves and a lack of CGRP-labeled nerves. As to the neuropeptidergic innervation of vessels, the number of VIP-containing nerves was modest, while, of the other neuropeptide-containing nerves under study, only few (SP and CGRP) to very few (NPY) nerves were observed. As to the nitrergic innervation, nNOS-containing nerves were very few close to secretory cells and even absent around vessels. Conclusion: The various innervation patterns may suggest potential transmission mechanisms involved in secretory and vascular responses of the major sublingual gland