Self-Organized Monitoring in Ad-Hoc Networks

We propose in this paper a self-organized monitoring architecture for mobile ad-hoc networks based on a selective scheme where subsets of nodes are managed. These nodes are determined based on their network behavior in order to favor subsets of well-connected nodes. The key idea is to relax the requirements of the management plane, and to use these manageable subsets to monitor the performance of the overall network. We therefore propose a new performance metric to be monitored, in order to estimate the capability of ad-hoc nodes to communicate end-to-end in the network. Extensive simulations show how different parameters affect this metric.     

Multifractal analysis of non-conformal repellers: a model case

For a model class of repellers of non-conformal expanding maps, we obtain sharp lower bounds for the dimension spectra of the Birkhoff averages of a Hölder continuous function. As in the well-studied case of conformal dynamics, the bounds are also expressed here in terms of the thermodynamic formalism.     

The influence of some vegetable extracts on the in vitro adherence of mouse and human lymphocytes to nylon fibers

We found that the total watery extracts obtained from roots of various plants such as Symphytum officinale, Phytolacca americana etc, precipitate human glycoproteins, agglutinate sheep red blood cells (SRBC) and stimulate lymphocyte adherence to nylon fibers. Five out of seven extracts precipitated human gammaglobulins and one of seven obviously agglutinate SRBC. If these cells were pretreated with rabbit antibodies against SRBC, all extracts agglutinated the cells at various degrees of intensity, the most active being Phytolacca americana. The adherence of mouse but not human lymphocytes to nylon fibers was stimulated by extracts of Symphytum officinale and Phytolacca americana. This process was neither stimulated nor inhibited by Mannose (Man), Galactose (Gal), Glucose (Glc), N-acethyl Galactose (GalNAc) and N-acethyl Glucose (Glc-NAc). These biological effects of the plant extracts could be the expression of a lectin-like ability to bind various sugars other than those mentioned. The results suggest the possibility of using different extracts as means to point out the presence in serum or at the cellular level of some carbohydrates influencing the cellular adhesion, phenomenon which plays an important role in the functions of hematopoietic cells.     

Turbulent Details Simulation for SPH Fluids via Vorticity Refinement

A major issue in smoothed particle hydrodynamics (SPH) approaches is the numerical dissipation during the projection process, especially under coarse discretizations. High‐frequency details, such as turbulence and vortices, are smoothed out, leading to unrealistic results. To address this issue, we introduce a vorticity refinement (VR) solver for SPH fluids with negligible computational overhead. In this method, the numerical dissipation of the vorticity field is recovered by the difference between the theoretical and the actual vorticity, so as to enhance turbulence details. Instead of solving the Biot‐Savart integrals, a stream function, which is easier and more efficient to solve, is used to relate the vorticity field to the velocity field. We obtain turbulence effects of different intensity levels by changing an adjustable parameter. Since the vorticity field is enhanced according to the curl field, our method can not only amplify existing vortices, but also capture additional turbulence. Our VR solver is straightforward to implement and can be easily integrated into existing SPH methods.     

A new approach to predict ulcerative colitis activity through standard clinical–biological parameters using a robust neural network model

Neural Computing and Applications - Colonoscopy is the “gold” standard for evaluating disease activity in ulcerative colitis (UC). An important area of research is finding a...     

Generating phenotypical erroneous human behavior to evaluate human–automation interaction using model checking

Breakdowns in complex systems often occur as a result of system elements interacting in unanticipated ways. In systems with human operators, human–automation interaction associated with both normative and erroneous human behavior can contribute to such failures. Model-driven design and analysis techniques provide engineers with formal methods tools and techniques capable of evaluating how human behavior can contribute to system failures. This paper presents a novel method for automatically generating task analytic models encompassing both normative and erroneous human behavior from normative task models. The generated erroneous behavior is capable of replicating Hollnagel's zero-order phenotypes of erroneous action for omissions, jumps, repetitions, and intrusions. Multiple phenotypical acts can occur in sequence, thus allowing for the generation of higher order phenotypes. The task behavior model pattern capable of generating erroneous behavior can be integrated into a formal system model so that system safety properties can be formally verified with a model checker. This allows analysts to prove that a human–automation interactive system (as represented by the model) will or will not satisfy safety properties with both normative and generated erroneous human behavior. We present benchmarks related to the size of the statespace and verification time of models to show how the erroneous human behavior generation process scales. We demonstrate the method with a case study: the operation of a radiation therapy machine. A potential problem resulting from a generated erroneous human action is discovered. A design intervention is presented which prevents this problem from occurring. We discuss how our method could be used to evaluate larger applications and recommend future paths of development.