Measuring Complexity in an Aquatic Ecosystem

We apply formal measures of emergence, self-organization, homeostasis, autopoiesis and complexity to an aquatic ecosystem; in particular to the physiochemical component of an Arctic lake. These measures are based on information theory. Variables with an homogeneous distribution have higher values of emergence, while variables with a more heterogeneous distribution have a higher self-organization. Variables with a high complexity reflect a balance between change (emergence) and regularity/order (self-organization). In addition, homeostasis values coincide with the variation of the winter and summer seasons. Autopoiesis values show a higher degree of independence of biological components over their environment. Our approach shows how the ecological dynamics can be described in terms of information.Comment: 6 pages, to be published in Proceedings of the CCBCOL 2013, 2nd Colombian Computational Biology Congress, Springe

Status and Evaluation of Microwave Furnace Capabilities at NASA Glenn Research Center

The microwave (MW) furnace is a HY-Tech Microwave Systems, 2 kW 2.45 GHz Single Mode Microwave Applicator operating in continuous wave (CW) with variable power. It is located in Cleveland, Ohio at NASA Glenn Research Center. Until recently, the furnace capabilities had not been fully realized due to unknown failure that subsequently damaged critical furnace components. Although the causes of the problems were unknown, an assessment of the furnace itself indicated operational failure may have been partially caused by power quality. This report summarizes the status of the MW furnace and evaluates its capabilities in materials processing

Modelling diffuse instabilities in sands under drained conditions

This paper presents a criterion for detecting diffuse (homogeneous) instabilities in granular soils sheared under fully drained conditions. The criterion is based on bifurcation theory and applied to elasto-plasticity by allowing multiple incremental solutions in elasto-plastic soils, physically losing controllability of stress boundary conditions. Drained diffuse instabilities are poorly understood, and are induced by kinematic modes different from those observed in shear bands and liquefaction instabilities. Unlike shear bands, diffuse instabilities occur under fairly homogenous deformation modes and, unlike liquefaction, drained instabilities are not generated by the excess pore pressures. Recent experiments under drained constant shear report sudden homogeneous instabilities in samples of relatively dense and loose sands. The criterion presented in this paper is used in conjunction with an elasto-plasticity model for sands to predict and explain these reported drained instabilities. From a practical standpoint, these developments serve to expand the repertoire of potential instabilities that occur well before failure, and which have been reported in case studies of puzzling slope instability failures under fully drained conditions

Effect of frictional heat dissipation on the loss of soil strength

In the present paper through a shear test on a fully saturated granular medium, simulated by the discrete element method, the effect of the heat produced by friction on the internal pore water pressure is explored. It is found that the dissipated energy is enough to increase the pore pressure and reduce the soil strength. In adiabatic and impermeable conditions the heat builds up quickly inside the shear band, and the softening is more pronounced. It is found as well that for real geological materials, heat conduction is not enough to reduce the pore pressure, and the softening prevails. Nevertheless, it is observed that the hydraulic conduction may mitigate or completely eliminate the temperature growth inside the shear band. This result provides new understanding on the thermodynamic factors involved in the onset of catastrophic landslides

A method for outlier detection based on cluster analysis and visual expert criteria

Outlier detection is an important problem occurring in a wide range of areas. Outliers are the outcome of fraudulent behaviour, mechanical faults, human error, or simply natural deviations. Many data mining applications perform outlier detection, often as a preliminary step in order to filter out outliers and build more representative models. In this paper, we propose an outlier detection method based on a clustering process. The aim behind the proposal outlined in this paper is to overcome the specificity of many existing outlier detection techniques that fail to take into account the inherent dispersion of domain objects. The outlier detection method is based on four criteria designed to represent how human beings (experts in each domain) visually identify outliers within a set of objects after analysing the clusters. This has an advantage over other clustering-based outlier detection techniques that are founded on a purely numerical analysis of clusters. Our proposal has been evaluated, with satisfactory results, on data (particularly time series) from two different domains: stabilometry, a branch of medicine studying balance-related functions in human beings and electroencephalography (EEG), a neurological exploration used to diagnose nervous system disorders. To validate the proposed method, we studied method outlier detection and efficiency in terms of runtime. The results of regression analyses confirm that our proposal is useful for detecting outlier data in different domains, with a false positive rate of less than 2% and a reliability greater than 99%

Fabrication of Boron Nitride Fibers by Force Spinning Method

The unique multifunctional properties of boron nitride (BN) nanomaterials are identified as a parameter that would revolutionize electric propulsion in Aeronautics due to the lightweight ceramic with chemical inertness, high strength, high electrical resistivity and high thermal conductivity. Hexagonal BN (h-BN) nanofibers will enable new high-performance fibers that can be used in ceramic or polymer matrix composites, or thin films to provide revolutionary multifunctional ceramics for extreme environments and structures. Polymer derived h-BN materials have been previously demonstrated, providing an avenue to tailor properties of the ceramic end product. This effort also uses forcespinning (FS) technology that produces continuous non-woven nanofibers in a range of diameters depending on the processing parameters with a large production rate of 1 g/min allowing for manufacturing scale production. FTIR, SEM, TGA and XRD were used to characterize the materials in each processing steps