Transferable atomic multipole machine learning models for small organic molecules

Accurate representation of the molecular electrostatic potential, which is often expanded in distributed multipole moments, is crucial for an efficient evaluation of intermolecular interactions. Here we introduce a machine learning model for multipole coefficients of atom types H, C, O, N, S, F, and Cl in any molecular conformation. The model is trained on quantum chemical results for atoms in varying chemical environments drawn from thousands of organic molecules. Multipoles in systems with neutral, cationic, and anionic molecular charge states are treated with individual models. The models' predictive accuracy and applicability are illustrated by evaluating intermolecular interaction energies of nearly 1,000 dimers and the cohesive energy of the benzene crystal.Comment: 11 pages, 6 figure

Elasticity of polyelectrolyte multilayer microcapsules

We present a novel approach to probe elastic properties of polyelectrolyte multilayer microcapsules. The method is based on measurements of the capsule load-deformation curves with the atomic force microscope. The experiment suggests that at low applied load deformations of the capsule shell are elastic. Using elastic theory of membranes we relate force, deformation, elastic moduli, and characteristic sizes of the capsule. Fitting to the prediction of the model yields the lower limit for Young's modulus of the polyelectrolyte multilayers of the order of 1-100 MPa, depending on the template and solvent used for its dissolution. These values correspond to Young's modulus of an elastomer

A Visual Analytics Approach for User Behaviour Understanding through Action Sequence Analysis

Analysis of action sequence data provides new opportunities to understand and model user behaviour. Such data are often in the form of timestamped and labelled series of atomic user actions. Cyber security is one of the domains that show the value of the analysis of these data. Elaborate and specialised models of user-behaviour are desired for effective decision making during investigation of cyber threats. However, due to their complex nature, activity sequences are not yet well-exploited within cyber security systems. In this paper, we describe the initial phases of a visual analytics approach that aims to enable a rich understanding of user behaviour through the analysis of user activity sequences. First, we discuss a motivating case study and discuss a number of high level requirements as derived from a series of workshops within an ongoing research project. We then present the components of a visual analytics approach that constitutes a novel combination of ``action space'' analysis, pattern mining, and the interactive visual analysis of multiple sequences to take the initial steps towards a comprehensive understanding of user behaviour

Coarse-grained interaction potentials for polyaromatic hydrocarbons

Using Kohn-Sham density functional theory (KS-DFT), we have studied the interaction between various polyaromatic hydrocarbon molecules. The systems range from mono-cyclic benzene up to hexabenzocoronene (hbc). For several conventional exchange-correlation functionals potential energy curves of interaction of the $\pi$-$\pi$ stacking hbc dimer are reported. It is found that all pure local density or generalized gradient approximated functionals yield qualitatively incorrect predictions regarding structure and interaction. Inclusion of a non-local, atom-centered correction to the KS-Hamiltonian enables quantitative predictions. The computed potential energy surfaces of interaction yield parameters for a coarse-grained potential, which can be employed to study discotic liquid-crystalline mesophases of derived polyaromatic macromolecules

Understanding User Behaviour through Action Sequences: from the Usual to the Unusual

Action sequences, where atomic user actions are represented in a labelled, timestamped form, are becoming a fundamental data asset in the inspection and monitoring of user behaviour in digital systems. Although the analysis of such sequences is highly critical to the investigation of activities in cyber security applications, existing solutions fail to provide a comprehensive understanding due to the complex semantic and temporal characteristics of these data. This paper presents a visual analytics approach that aims to facilitate a user-involved, multi-faceted decision making process during the identification and the investigation of “unusual” action sequences. We first report the results of the task analysis and domain characterisation process. Then we describe the components of our multi-level analysis approach that comprises of constraint-based sequential pattern mining and semantic distance based clustering, and multi-scalar visualisations of users and their sequences. Finally, we demonstrate the applicability of our approach through a case study that involves tasks requiring effective decision-making by a group of domain experts. Although our solution here is tightly informed by a user-centred, domain-focused design process, we present findings and techniques that are transferable to other applications where the analysis of such sequences is of interest

Young's modulus of polyelectrolyte multilayers from microcapsule swelling

We measure Young's modulus of a free polyelectrolyte multilayer film by studying osmotically induced swelling of polyelectrolyte multilayer microcapsules filled with the polyelectrolyte solution. Different filling techniques and core templates were used for the capsule preparation. Varying the concentration of the polyelectrolyte inside the capsule, its radius and the shell thickness yielded an estimate of an upper limit for Young's modulus of the order of 100 MPa. This corresponds to an elastomer and reflects strong interactions between polyanions and polycations in the multilayer

VASABI: Hierarchical User Profiles for Interactive Visual User Behaviour Analytics

User behaviour analytics (UBA) systems offer sophisticated models that capture users’ behaviour over time with an aim to identify fraudulent activities that do not match their profiles. Making decisions based on such systems; however, requires an in-depth understanding of user behaviour both at an individual and at a group level where a group can consist of users with similar roles. We present a visual analytics approach to help analysts gain a comprehensive, multifaceted understanding of user behaviour at multiple levels. We take a user-centred approach to design a visual analytics framework supporting the analysis of collections of users and the numerous sessions of activities they conduct within digital applications. The framework is centred around the concept of hierarchical user profiles, where the profiles are built based on features derived from sessions they perform and visualised with task-informed designs to facilitate interactive exploration and investigation. We also present techniques to extract user tasks that summarise the behaviour and to cluster users according to these tasks for providing hierarchical overviews of groups of users along with individual users and the sessions they conduct. We externalise a series of analysis goals and tasks, and evaluate our methods through a number of use cases that demonstrate how these tasks are addressed. We observe that with the aid of interactive visual hierarchical user profiles, analysts were able to conduct exploratory and investigative analysis effectively, and able to understand the characteristics of user behaviour to make informed decisions whilst evaluating suspicious users and activities

SOCIAL CONFLICTS IN CHARITIES: REASONS, CONSEQUENCE SAND WAYS OF SOLVING THEM

The article deals with the origin of social conflicts of international charities by addressing to a science of conflictology, it also emphasizes the difference between egoism and altruism related motivation of the parties involved into a charity process; it argues about the charity act in terms of semiotics and shows the ways of solving these problems in accordance to cultural, social and psychological features which reflect the modern society

SOCIAL CONFLICTS IN CHARITIES: REASONS, CONSEQUENCE SAND WAYS OF SOLVING THEM

The article deals with the origin of social conflicts of international charities by addressing to a science of conflictology, it also emphasizes the difference between egoism and altruism related motivation of the parties involved into a charity process; it argues about the charity act in terms of semiotics and shows the ways of solving these problems in accordance to cultural, social and psychological features which reflect the modern society

Forces between elongated particles in a nematic colloid

Using molecular dynamics simulations we study the interactions between elongated colloidal particles (length to breath ratio ≫1) in a nematic host. The simulation results are compared to the results of a Landau–de Gennes elastic free energy. We find that depletion forces dominate for the sizes of the colloidal particles studied. The tangential component of the force, however, allows us to resolve the elastic contribution to the total interaction. We find that this contribution differs from the quadrupolar interaction predicted at large separations. The difference is due to the presence of nonlinear effects, namely, the change in the positions and structure of the defects and their annihilation at small separations