Modeling biological gradient formation: combining partial differential equations and Petri nets

Both Petri nets and differential equations are important modeling tools for biological processes. In this paper we demonstrate how these two modeling techniques can be combined to describe biological gradient formation. Parameters derived from partial differential equation describing the process of gradient formation are incorporated in an abstract Petri net model. The quantitative aspects of the resulting model are validated through a case study of gradient formation in the fruit fly.     

Communication‐Aware Information‐Gathering Experiments with an Unmanned Aircraft System

This paper presents single and multiaircraft flight experiments to assess an information‐theoretic path planning algorithm that incorporates sensing and communication to guide an unmanned aircraft. The communication is modeled with packet erasure channels for each link in a multihop mesh network. The planning objective is to maximize the mutual information between the target state and measurements received at a single base station from all aircraft. A novel unmanned aircraft system was developed to facilitate experiments with multiple unmanned aircraft utilizing multihop mesh networking. The value of communication‐aware planning was assessed through flight experiments with a single aircraft localizing a radio emitter. Additional experiments with two aircraft demonstrated and assessed the performance of the approach, showing that the improvement in sensing can be appreciable when utilizing multihop communication.     

Analytical modelling of multiservice switching networks with multiservice sources and resource management mechanisms

In this paper, we presents an analytical link capacity and outage performance analysis of downlink multiuser diversity (MUD) in multiple-input multiple-output (MIMO) system employing maximal-ratio combining (MRC) with transmit antenna selection (TAS) in the presence of imperfect channel state information (CSI) due to feedback delay over Rayleigh fading channels. The unified achievable analysis is appropriate for MUD–MIMO with TAS/MRC systems in which effective output signal-to-noise ratio (SNR) is specified as highest order statistic of chi-square distribution. Based on this framework, the closed-form channel capacity and outage probability expressions are examined for the MUD–MIMO exploiting TAS/MRC with normalized SNR based scheduling in heterogeneous wireless networks. Further, we derive approximate upper bound capacity as well as capacity at high SNR and low SNR region under delayed feedback CSI. The upper and lower bound of outage probability under delayed feedback CSI is also evaluated. Thereafter the impact of feedback delay and antenna structures with significance on the consideration of MUD on the performance of the system has been analyzed.     

A study on using data clustering for feature extraction to improve the quality of classification

There is a certain belief among data science researchers and enthusiasts alike that clustering can be used to improve classification quality. Insofar as this belief is fairly uncontroversial, it is also very general and therefore produces a lot of confusion around the subject. There are many ways of using clustering in classification and it obviously cannot always improve the quality of predictions, so a question arises, in which scenarios exactly does it help? Since we were unable to find a rigorous study addressing this question, in this paper, we try to shed some light on the concept of using clustering for classification. To do so, we first put forward a framework for incorporating clustering as a method of feature extraction for classification. The framework is generic w.r.t. similarity measures, clustering algorithms, classifiers, and datasets and serves as a platform to answer ten essential questions regarding the studied subject. Each answer is formulated based on a separate experiment on 16 publicly available datasets, followed by an appropriate statistical analysis. After performing the experiments and analyzing the results separately, we discuss them from a global perspective and form general conclusions regarding using clustering as feature extraction for classification.

     

Phenolic compounds isolated from bitter lupine seeds and their inhibitory effects on germination and seedling growth of lettuce

The phenolic acids, including 4-hydroxybenzoic and 4-hydroxycinnamic acids, and their derivatives, such as 6,7-dihydroxycoumarin and 1,2-dihydroxybenzene, were isolated from bitter lupine seeds and were identified using gas chromatography-mass spectrometry. These compounds inhibited lettuce seed germination in the first 24 hr after sowing, but after 72 hr germination was comparable with that of the control. However, very strong suppression of seedling growth, especially the roots, was observed for higher concentrations of the lupine seed fractions containing phenolic acids. Effects observed in the lettuce germination bioassays were compared with those produced by nine pure phenolic acids previously identified in the mixture. The ethyl acetate fraction from lupine seed extract inhibited seedling growth as effectively as pure 1,2-dihydroxybenzene, the strongest inhibitor of the pure phenolic compounds studied. The possible reason for this could be the synergistic effect created in the mixture of phenolic compounds isolated from the extract.     

Influence of progressive surface oxidation of nitrogen-containing carbon on its electrochemical behaviour in phosphate buffer solutions

The effects of the nitric acid surface oxidation of nitrogen-containing carbons (SCN-type) on the chemical structure as well as the electrochemical properties of powdered electrodes prepared from them were studied. The oxidation efficiency was dependent on the duration of the oxidative modification. The surface chemistry was characterized using standard neutralization techniques and spectroscopic methods (FTIR and XPS). Electrochemically active surface groups obtained on carbon materials during oxidation were investigated by cyclic voltammetry. Some noteworthy relations between the electrochemical activity of carbon electrode material and the degree of surface oxidation are reported.     

Design study of printer nozzle spray dryer by computational fluid dynamics modeling

Abstract

Milk powder production is one of the most energy-consuming processes in the dairy industry. To reduce production costs and increase spray dryer efficiency, the EU sponsored an international project named ENTHALPY. One of the results of the project was the development of mathematical models and computational fluid dynamics simulation methodology for the milk spray-drying process. This article introduces the methodology of CFD model development and presents simulation results as the basis for further drying tower design optimization. The CFD simulations were performed for a new design of monodisperse multistream atomizer. As a result of the CFD simulation, sets of parameters such as drying efficiency, protein thermal degradation, collision frequency, and wall deposition were obtained.     

Surface selective chemical deposition of polyanilines

We report on chemical in situ deposition of poly(o-anisidine) and polyaniline on bare and thiol-modified gold. It is shown that the process of o-anisidine polymerization is initiated on the metal surface and in consequence it is very sensitive to modifications of the coating substrate. Polyaniline deposited under the same conditions does not reveal such sensitivity as the polymer is forming in the polymerization solution and is subsequently physisorbed on the surface. Thus, the substrate itself has little effect on the polymer deposition rate. The large differences in deposition rates of poly(o-anisidine) make this material promising in preparation of polymeric patterns using lithographic methods.     

Computer Aided Tolerancing (CAT) platform for the design of assemblies under external and internal forces

Due to the stochastic nature of manufacturing processes, the functionality of mechanical assemblies is subject to variation defined by tolerances and manufacturing process characteristics. In many assemblies, functionality is also dependent on external and internal forces. Numerous Computer Aided Tolerancing (CAT) tools have been proposed that address tolerance analysis problems in complex mechanical assemblies; however current tools do not accommodate a general class of problem where the functionality of a design is fundamentally dependent on the effects of external and internal forces. This research addresses the limitation of CAT tools to accommodate assemblies under loading by developing a tolerance analysis platform which integrates CAD, CAE and statistical analysis tools using Process Integration and Design Optimisation (PIDO) software capabilities. The platform extends the capabilities of traditional CAT tools by enabling tolerance analysis of assemblies in which assembly characteristics are dependent on external and internal forces. To demonstrate the capabilities of the developed platform, examples of tolerance analysis problems involving external forces (compliance) and internal forces (multi-body dynamics) are presented.     

A direct solver with reutilization of LU factorizations for h-adaptive finite element grids with point singularities

This paper describes a direct solver algorithm for a sequence of finite element meshes that are $h$-refined towards one or several point singularities. For such a sequence of grids, the solver delivers linear computational cost $O\left(N\right)$ in terms of CPU time and memory with respect to the number of unknowns $N$. The linear computational cost is achieved by utilizing the recursive structure provided by the sequence of $h$-adaptive grids with a special construction of the elimination tree that allows for reutilization of previously computed partial LU (or Cholesky) factorizations over the entire unrefined part of the computational mesh. The reutilization technique reduces the computational cost of the entire sequence of $h$-refined grids from $O\left(N^2\right)$ down to $O\left(N\right)$. Theoretical estimates are illustrated with numerical results on two- and three-dimensional model problems exhibiting one or several point singularities.