Practical Application of the Probabilistic‐Statistical Model of the Suspension Separation in Hydrocyclones

An effective practical approach that allows not only a significant reduction in the scope of practical experiments in the course of studying suspension separation processes in hydrocyclones, but also makes it possible to assess the intensity of random components of the processes and define the interrelation between such components and hydrodynamics of flows in a hydrocyclone is presented. Within the frames of the developed probabilistic‐statistical model of suspension separation in hydrocyclones on the basis of statistical self‐similarity properties, a relationship was found between determined and random components of the processes. This allowed transitioning from three‐parameter probability density functions for suspension particles in hydrocyclones to two‐parameter functions; thus significantly improving the efficiency of practical application of the developed model.     

Decision Making Effectiveness in Wildfire Incident Management Teams

During large scale wildfires, suppression activities are carried out under the direction of an Incident Management Team (IMT). The aim of the research was to increase understanding of decision processes potentially related to IMT effectiveness. An IMT comprises four major functions: Command, Operations, Planning, and Logistics. Four methodologies were used to study IMT processes: computer simulation experiments; analyses of wildfire reports; interviews with IMT members; and cognitive ethnographic studies of IMTs. Three processes were important determinants of IMT effectiveness: information management and cognitive overload; matching component function goals to overall goals; and team metacognition to detect and counter task‐disruptive developments. These processes appear to be complex multi‐person analogues of individual Incident Command processes identified previously. The findings have implications for issues such as: creating IMTs; training IMTs; managing IMTs; and providing decision support to IMTs.     

Straightforward modeling of dynamic I–V characteristics for microwave FETs

This work presents a straightforward approach aimed at modeling the dynamic I–V characteristics of microwave active solid‐state devices. The drain‐source current generator represents the most significant source of nonlinearity in a transistor and, therefore, its correct modeling is fundamental to predict accurately the current and voltage waveforms under large‐signal operation. The proposed approach relies on using a small set of low‐frequency time‐domain waveform measurements combined with numerical optimization‐based estimation of the nonlinear model parameters. The procedure is applied to a gallium nitride HEMT and silicon FinFET. The effectiveness of the modeling procedure in terms of prediction accuracy and generalization capability is demonstrated by validation of the extracted models under operating conditions different than the ones used for the parameters estimation. Good agreement between measurements and model simulations is achieved for both technologies and in both low‐ and high‐frequency range. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:109–116, 2014.     

Computational Aspects of Uncertainty Profiles and Angel-Daemon Games

We analyze the complexity of equilibria problems for a class of strategic zero-sum games, called angel-daemon games. Those games were introduced to asses the performance of the execution of a web orchestration on a moderate faulty or under stress environment. Angel-daemon games are a natural example of zero-sum games whose representation is naturally succinct. We show that the problems of deciding the existence of a pure Nash equilibrium or of a dominant strategy for a given player are ${\Sigma}^{p}_{2}$ -complete. Furthermore, computing the value of an angel-daemon game is EXP-complete. Thus, our results match the already known classification of the corresponding problems for the generic families of succinctly represented games with exponential number of actions.     

Classification of honeys by principal component analysis on the basis of chemical and physical parameters

Summary Eighteen chemical and physical parameters of nectar and honeydew honeys were determined and the results were analysed statistically by the method of principal component analysis. On the plots of principal component loadings, the honeys were divided into the following groups: (1) acacia honey; (2) rape honey; (3) linden, floral (nectar coming from various plants) and heather honeys; (4) honeydew honey. The samples which were a blend of nectar and honeydew honeys may be considered as a separate group between 3 and 4. The most important first principal component was strongly associated with the value of electrical conductivity, the contents of ash, free acids and proline, as well as with the pH and the diastase number. The principal component loadings and linear correlation suggested that these parameters contributed much more to the classification of honeys than apparent reducing sugars, apparent sucrose, mono-, di-, and trisaccharides, glucose and fructose. The classification of honeys by the method of principal component analysis may serve as an additional tool in specifying samples on the basis of their chemical composition.

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Klassifizierung von Honigen durch chemische und physikalische Parameter mit Hilfe der Hauptkomponentenanalyse

Zusammenfassung 18 chemische und physikalische Parameter der Nektar- und Honigtauhonige wurden bestimmt und die Ergebnisse statistisch mit Hilfe der Hauptkomponentenanalyse ausgewertet. Danach konnten die Honige in folgende Gruppen unterteilt werden: 1) Akazienhonige, 2) Rapshonige, 3) Linden-, Blüten-und Heidehonige, 4) Honigtauhonige. Zwischen dem Nektarhonig und Honigtauhonig lagen wahrscheinlich die Proben von Mischhonigen aus Blüten- und Waldtracht. Die bedeutendste erste Hauptkomponente war mit folgenden Parametern verbunden: elektrischer Leitfähigkeitswert und Aschegehalt, Gehalt an freien Säuren und Prolin sowie der pH-Wert und Diastasezahl. Aufgrund der Hauptkomponentenladungen und der linearen Korrelation kann angenommen werden, daß diese Parameter für die Honigklassifizierung von größerer Bedeutung sind als der Gehalt an reduzierenden Zuckern, scheinbarer Saccharose, Mono-, Di- und Trisaccharide, Glucose und Fructose. Die Klassifizierung der Honige mit Hilfe der Hauptkomponentenanalyse kann bei der Spezifikation einer Honigprobe aufgrund ihrer chemischen Zusammensetzung von Nutzen sein.

     

Surface-enhanced Raman scattering nanosensors for <Emphasis Type="Italic">in vivo</Emphasis> detection of nucleic acid targets in a large animal model

Although nanotechnology has led to important advances in in vitro diagnostics, the development of nanosensors for in vivo detection remains very challenging. Here, we demonstrated the proof-of-principle of in vivo detection of nucleic acid targets using a promising type of surface-enhanced Raman scattering (SERS) nanosensor implanted in the skin of a large animal model (pig). The in vivo nanosensor used in this study involves the “inverse molecular sentinel” detection scheme using plasmonics-active nanostars, which have tunable absorption bands in the near infrared region of the “tissue optical window”, rendering them efficient as an optical sensing platform for in vivo optical detection. Ex vivo measurements were also performed using human skin grafts to demonstrate the detection of SERS nanosensors through tissue. In this study, a new core–shell nanorattle probe with Raman reporters trapped between the core and shell was utilized as an internal standard system for self-calibration. These results illustrate the usefulness and translational potential of the SERS nanosensor for in vivo biosensing.

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A Fast Explicit Operator Splitting Method for Passive Scalar Advection

The dispersal and mixing of scalar quantities such as concentrations or thermal energy are often modeled by advection-diffusion equations. Such problems arise in a wide variety of engineering, ecological and geophysical applications. In these situations a quantity such as chemical or pollutant concentration or temperature variation diffuses while being transported by the governing flow. In the passive scalar case, this flow prescribed and unaffected by the scalar. Both steady laminar and complex (chaotic, turbulent or random) time-dependent flows are of interest and such systems naturally lead to questions about the effectiveness of the stirring to disperse and mix the scalar. The development of reliable numerical methods for advection-diffusion equations is crucial for understanding their properties, both physical and mathematical. In this paper, we extend a fast explicit operator splitting method, recently proposed in (A. Chertock, A. Kurganov, G. Petrova, Int. J. Numer. Methods Fluids 59:309–332, 2009), for solving deterministic convection-diffusion equations, to the problems with random velocity fields and singular source terms. A superb performance of the method is demonstrated on several two-dimensional examples.