A labeling algorithm to recognize a line digraph and output its root graph

In this short note we present a very efficient, linear time algorithm for the recognition of line digraphs. The algorithm is based on a reformulation of the characterization of line digraphs proved by Harary and Norman.     

Solvent Screening for Solubility Enhancement of Theophylline in Neat,Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning

Theophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally studied binary systems, the one containing DMSO with water in unimolar proportions was found to be the most effective in theophylline dissolution. Likewise, for NADES, the addition of water (0.2 molar fraction) resulted in increased solubility compared to pure eutectics, with the highest solubilisation potential offered by the composition of choline chloride with glycerol. The ensemble of Statistica Automated Neural Networks (SANNs) developed using intermolecular interactions in pure systems has been found to be a very accurate model for solubility computations. This machine learning protocol was also applied as an extensive screening for potential solvents with higher solubility of theophylline. Such solvents were identified in all three subgroups, including neat solvents, binary mixtures and ternary NADES systems. Some methodological considerations of SANNs applications for future modelling were also provided. Although the developed protocol is focused exclusively on theophylline solubility, it also has general importance and can be used for the development of predictive models adequate for solvent screening of other compounds in a variety of systems. Formulation of such a model offers rational guidance for the selection of proper candidates as solubilisers in the designed solvents screening.     

The Role of TRPM2 in Endothelial Function and Dysfunction

The transient receptor potential (TRP) melastatin-like subfamily member 2 (TRPM2) is a non-selective calcium-permeable cation channel. It is expressed by many mammalian tissues, including bone marrow, spleen, lungs, heart, liver, neutrophils, and endothelial cells. The best-known mechanism of TRPM2 activation is related to the binding of ADP-ribose to the nudix-box sequence motif (NUDT9-H) in the C-terminal domain of the channel. In cells, the production of ADP-ribose is a result of increased oxidative stress. In the context of endothelial function, TRPM2-dependent calcium influx seems to be particularly interesting as it participates in the regulation of barrier function, cell death, cell migration, and angiogenesis. Any impairments of these functions may result in endothelial dysfunction observed in such conditions as atherosclerosis or hypertension. Thus, TRPM2 seems to be an attractive therapeutic target for the conditions connected with the increased production of reactive oxygen species. However, before the application of TRPM2 inhibitors will be possible, some issues need to be resolved. The main issues are the lack of specificity, poor membrane permeabilization, and low stability in in vivo conditions. The article aims to summarize the latest findings on a role of TRPM2 in endothelial cells. We also show some future perspectives for the application of TRPM2 inhibitors in cardiovascular system diseases.     

Two implementation relations and the correctness of communicating replicated processes

This paper studies the correctness of distributed systems made up of replicated processes that communicate by message passing. Processes are described within the divergence model of CSP. The notion of correctness introduced is based on a relation that formally expresses the conformance of an implementation process with the target process it is intended to implement. A weak and a strong version of the relation are introduced, aimed at treating acyclic and cyclic process networks respectively. Both allow the study of (total) correctness and may cope with non-deterministic targets and implementations.We then show how a target process may be implemented (in the formal sense introduced) by replicating it in a set of copies, a majority of which is non-faulty.     

The Dynamic Emission Zone in Sandwich Polymer Light‐Emitting Electrochemical Cells

In light‐emitting electrochemical cells (LECs), the position of the emission zone (EZ) is not predefined via a multilayer architecture design, but governed by a complex motion of electrical and ionic charges. As a result of the evolution of doped charge transport layers that enclose a dynamic intrinsic region until steady state is reached, the EZ is often dynamic during turn‐on. For thick sandwich polymer LECs, a continuous change of the emission color provides a direct visual indication of a moving EZ. Results from an optical and electrical analysis indicate that the intrinsic zone is narrow at early times, but starts to widen during operation, notably well before the electrical device optimum is reached. Results from numerical simulations demonstrate that the only precondition for this event to occur is that the mobilities of anions (μ_a) and cations (μ_c) are not equal, and the direction of the EZ shift dictates μ_c > μ_a. Quantitative ion profiles reveal that the displacement of ions stops when the intrinsic zone stabilizes, confirming the relation between ion movement and EZ shift. Finally, simulations indicate that the experimental current peak for constant‐voltage operation is intrinsic and the subsequent decay does not result from degradation, as commonly stated.     

Inline method of droplet and particle size distribution analysis in dilute disperse systems

In the present article a measurement method of particle size distributions (PSD) in industrial installations which use a dispersed phase of low concentration (like spray dryers or spray scrubbers) is introduced. A new type of inline-measurement system has been developed and designed to work in spray drying conditions. A standard digital camera is used to record shadows of flowing particles inside the spray drying chamber. Collected images were analyzed by a newly developed software which recognizes particles only in the focus area and eliminates several types of artifacts. The constructed prototype of the PSD inline-analyzer was installed and used to monitor large laboratory scale spray dryer. All data collected by the designed system during the spray drying experiments were compared with data measured with an offline reference system to show accuracy of the new measurement technique.     

CFD modelling of moisture evaporation in an industrial dispersed system

A methodology is presented here for the mathematical modelling of moisture evaporation in a dispersed system in an industrial tower. An empirical model using characteristic drying curves was applied to calculate moisture evaporation from a droplet and particle. A simple method was developed to calculate the agglomeration process of the dispersed phase in the drying towers, using transient functions between the initial and final particle size distributions, at the nozzle and in the final product. The developed model and simulation results were validated on the basis of industrial spray tower experiments. High instability of the airflow due to the geometry of the dryer and the construction of the air inlets was observed. The general methodology applied within this CFD model is universal, and can be applied to the scaling-up of installations for dewatering in dispersed systems in order to determine configurations of feeding systems and control the product quality and safety of the process.     

The VFO-Driven Motion Planning and Feedback Control in Polygonal Worlds for a Unicycle with Bounded Curvature of Motion

Integrated motion planning and control for the purposes of maneuvering mobile robots under state- and input constraints is a problem of vital practical importance in applications of mobile robots such as autonomous transportation. Those constraints arise naturally in practice due to specifics of robot mechanical construction and the presence of obstacles in motion environment. In contrast to approaches focusing on feedback control design under the assumption of given reference motion or motion planning with neglection of subsequent feedback motion execution, we adopt a controller-driven motion planning paradigm, which has recently gained attention of many researchers. It postulates design of motion planning algorithms dedicated to specific feedback control policies, which compute a sequence of feedback control subtasks instead of classically planned open-loop controls or parametric paths. In this spirit, we propose a motion planning algorithm driven by the VFO (Vector Field Orientation) control law for the waypoint-following task. Presented analysis of the VFO control law reveals its beneficial properties, which are subsequently utilized to solve a generally nonlinear and non-convex optimal motion planning problem by formulating it as a mixed-integer linear program (MILP). The solution proposed in this paper yields a waypoint sequence, which is designed for execution by application of the VFO control law to drive a robot to a prescribed final configuration under an input constraint imposed by bounded curvature of robot motion and state constraints resulting from a convex decomposition of task space. Satisfaction of these constraints is guaranteed analytically and exactly, i.e., without utilization of numerical approximations. Moreover, for a given discrete set of possible waypoint orientations, the proposed algorithm computes plans optimal w.r.t. given cost functional, which can be any convex linear combination of quantities such as robot path length, curvature of robot motion, distance to imposed state constraints, etc. Furthermore, the planning algorithm exploits the possibility of both forward or backward movement of the robot to allow maneuvering in demanding environments. Generated waypoint sequences are a compact representation of a motion plan, which can be immediately executed with the VFO controller without any additional post-processing. Validity of the proposed approach has been confirmed by simulation studies and experimental motion execution with a laboratory-scale mobile robot.     

Learning Detail Transfer based on Geometric Features

The visual richness of computer graphics applications is frequently limited by the difficulty of obtaining high‐quality, detailed 3D models. This paper proposes a method for realistically transferring details (specifically, displacement maps) from existing high‐quality 3D models to simple shapes that may be created with easy‐to‐learn modeling tools. Our key insight is to use metric learning to find a combination of geometric features that successfully predicts detail‐map similarities on the source mesh; we use the learned feature combination to drive the detail transfer. The latter uses a variant of multi‐resolution non‐parametric texture synthesis, augmented by a high‐frequency detail transfer step in texture space. We demonstrate that our technique can successfully transfer details among a variety of shapes including furniture and clothing.