Geometric parameters of shoreface profiles of Laptev Sea erosion coast (Table 1)

Field investigations of the Laptev Sea shoreface morphology were carried out (1) off erosional shores composed of unconsolidated sediments, (2) off the modern delta shores of the Lena River, and (3) off rocky shores. It was found that profiles off erosional shores had a concave shape. This shape is not well described by commonly applied power functions, a feature, which is in disagreement with the generally accepted concept of the equilibrium shape of shoreface profiles. The position of the lower shoreface boundary is determined by the elevation of the coastal lowland inundated during the last transgression (at -5 to -10 m) and may easily be recognized by a sharp, an order of magnitude decrease in the mean inclination of the sea floor. The mean shoreface inclination depends on sediment grain-size and ranges from 0.0022 to 0.033. The concave shape of the shoreface did not change substantially during the last 20-30 years, which indicates that shoreline retreat did not slow down and hence suggests continued intensive coastal erosion in the 21st century. The underwater part of the Lena River delta extends up to 35 km offshore. Its upper part is formed by a shallow and up to 18-km wide bench, which reaches depths of 2-3 m along the outer edge. The evolution of the delta was irregular. Whereas some parts of the delta are advancing rapidly (58 m/year), other parts are eroding. Comparison of measured profiles with older bathymetric data gave an opportunity to evaluate the changes of the underwater delta over past decades. Bathymetric surveys of the seabed around the delta can thus contribute towards a quantification of the sediment budget of the river-sea system. In addition, some sections of the Laptev Sea coast are composed of bedrock that has a comparatively low resistance to wave erosion. These sections may supply a considerable amount of sediment, especially if the cliffs are high. This source must therefore also be taken into account when assessing the contribution of shore erosion to the Laptev Sea sediment budget.

Atmospheric, oceanic and hydrological polar motion excitation mechanisms based on a combination of geometric and gravimetric space observations

The goal of our study is to determine accurate time series of geophysical Earth rotation excitations to learn more about global dynamic processes in the Earth system. For this purpose, we developed an adjustment model which allows to combine precise observations from space geodetic observation systems, such as Satellite Laser Ranging (SLR), Global Navigation Satellite Systems (GNSS), Very Long Baseline Interferometry (VLBI), Doppler Orbit determination and Radiopositioning Integrated on Satellite (DORIS), satellite altimetry and satellite gravimetry in order to separate geophysical excitation mechanisms of Earth rotation. Three polar motion time series are applied to derive the polar motion excitation functions (integral effect). Furthermore we use five time variable gravity field solutions from Gravity Recovery and Climate Experiment (GRACE) to determine not only the integral mass effect but also the oceanic and hydrological mass effects by applying suitable filter techniques and a land-ocean mask. For comparison the integral mass effect is also derived from degree 2 potential coefficients that are estimated from SLR observations. The oceanic mass effect is also determined from sea level anomalies observed by satellite altimetry by reducing the steric sea level anomalies derived from temperature and salinity fields of the oceans. Due to the combination of all geodetic estimated excitations the weaknesses of the individual processing strategies can be reduced and the technique-specific strengths can be accounted for. The formal errors of the adjusted geodetic solutions are smaller than the RMS differences of the geophysical model solutions. The improved excitation time series can be used to improve the geophysical modeling.

A Mathematical Representation of "Excitement" in Games from the Viewpoint of a Neutral Audience

Researchers have long believed the concept of "excitement" in games to be subjective and difficult to measure. This paper presents the development of a mathematically computable index that measures this concept from the viewpoint of an audience. One of the key aspects of the index is the differential of the probability of "winning" before and after one specific "play" in a given game. If the probability of winning becomes very positive or negative by that play, then the audience will feel the game to be "exciting." The index makes a large contribution to the study of games and enables researchers to compare and analyze the "excitement" of various games. It may be applied to many fields especially the area of welfare economics, ranging from allocative efficiency to axioms of justice and equity.

A Mathematical Representation of "Excitement" in Games: A Contribution to the Theory of Game Systems

Researchers have long believed the concept of "excitement" in games to be subjective and difficult to measure. This paper presents the development of a mathematically computable index that measures the concept from the viewpoint of an audience and from that of a player. One of the key aspects of the index is the differential of the probability of "winning" before and after one specific "play" in a given game. The index makes a large contribution to the study of games and enables researchers to compare and analyze the “excitement” of various games. It may be applied in many fields, especially the area of welfare economics, and applications may range from those related to allocative efficiency to axioms of justice and equity.

Project management competence analysis in rural communities through territorial representation: application to Aymara women communities in Puno (Peru)

The acquisition of technical, contextual and behavioral competences is a prerequisite for sustainable development and strengthening of rural communities. Territorial display of the status of these skills helps to design the necessary learning, so its inclusion in planning processes is useful for decision making. The article discusses the application of visual representation of competences in a rural development project with Aymara women communities in Peru. The results show an improvement of transparency and dialogue, resulting in a more successful project management and strengthening of social organization.

Geometric Integrability of the Camassa-Holm Equation. II

It is known that the Camassa–Holm (CH) equation describes pseudo-spherical surfaces and that therefore its integrability properties can be studied by geometrical means. In particular, the CH equation admits nonlocal symmetries of “pseudo-potential type”: the standard quadratic pseudo-potential associated with the geodesics of the pseudo-spherical surfaces determined by (generic) solutions to CH, allows us to construct a covering π of the equation manifold of CH on which nonlocal symmetries can be explicitly calculated. In this article, we present the Lie algebra of (first-order) nonlocal π-symmetries for the CH equation, and we show that this algebra contains a semidirect sum of the loop algebra over sl(2,R) and the centerless Virasoro algebra. As applications, we compute explicit solutions, we construct a Darboux transformation for the CH equation, and we recover its recursion operator. We also extend our results to the associated Camassa–Holm equation introduced by J. Schiff.

Geometric characteristics of conics in Bézier form

Derive coordinate-free expressions for geometric characteristics of conics written in Bézier form in terms of their control points and weights.

Neuromorphic Detection of Vowel Representation Spaces

In this paper a layered architecture to spot and characterize vowel segments in running speech is presented. The detection process is based on neuromorphic principles, as is the use of Hebbian units in layers to implement lateral inhibition, band probability estimation and mutual exclusion. Results are presented showing how the association between the acoustic set of patterns and the phonologic set of symbols may be created. Possible applications of this methodology are to be found in speech event spotting, in the study of pathological voice and in speaker biometric characterization, among others.

Aerodynamic study of airfoils geometric imperfections at low Reynolds number

The interest of this study is based on the observation that some manufacturing processes of various vehicles wings, such as unmanned aerial vehicle (UAV), or blades, such as wind turbine blades, or other devices that use aerodynamic profiles, produce imperfections in the leading edge or open trailing edge with bigger thickness than original airfoil, because, for example, they are manufactured in two parts, top surface and bottom surface and subsequently joined. In this last step might appear a sliding between the top surface and the bottom surface having a small step on the leading edge or a small thickness gain can occur on the trailing edge. Normally these imperfections are corrected through a refill and/or sanding processes using many hours of manual labor. Therefore the initial objective of this research is to determine the level of influence in the aerodynamic characteristics at low Reynolds numbers (Lissaman, 1981, Carmichael, 1981, Nagamatsu and Cuche, 1981, Schmitz, 1957, Cebeci, 1989, Mueller and Batill, 1982) of these imperfections in the manufacture, and determine whether there may be a value for which it would not be necessary to correct them

Synchronization waves in geometric networks

We report synchronization of networked excitable nodes embedded in a metric space, where the connectivity properties are mostly determined by the distance between units. Such a high clustered structure, combined with the lack of long-range connections, prevents full synchronization and yields instead the emergence of synchronization waves. We show that this regime is optimal for information transmission through the system, as it enhances the options of reconstructing the topology from the dynamics. Measurements of topological and functional centralities reveal that the wave-synchronization state allows detection of the most structurally relevant nodes from a single observation of the dynamics, without any a priori information on the model equations ruling the evolution of the ensemble

Dense Map Inference with User-Defined Priors: From Priorlets to Scan Eigenvariations

When mapping is formulated in a Bayesian framework, the need of specifying a prior for the environment arises naturally. However, so far, the use of a particular structure prior has been coupled to working with a particular representation. We describe a system that supports inference with multiple priors while keeping the same dense representation. The priors are rigorously described by the user in a domain-specific language. Even though we work very close to the measurement space, we are able to represent structure constraints with the same expressivity as methods based on geometric primitives. This approach allows the intrinsic degrees of freedom of the environment’s shape to be recovered. Experiments with simulated and real data sets will be presented

A geometric characterization of the upper bound for the span of the jones polynomial

Let D be a link diagram with n crossings, sA and sB be its extreme states and |sAD| (respectively, |sBD|) be the number of simple closed curves that appear when smoothing D according to sA (respectively, sB). We give a general formula for the sum |sAD| + |sBD| for a k-almost alternating diagram D, for any k, characterizing this sum as the number of faces in an appropriate triangulation of an appropriate surface with boundary. When D is dealternator connected, the triangulation is especially simple, yielding |sAD| + |sBD| = n + 2 - 2k. This gives a simple geometric proof of the upper bound of the span of the Jones polynomial for dealternator connected diagrams, a result first obtained by Zhu [On Kauffman brackets, J. Knot Theory Ramifications6(1) (1997) 125–148.]. Another upper bound of the span of the Jones polynomial for dealternator connected and dealternator reduced diagrams, discovered historically first by Adams et al. [Almost alternating links, Topology Appl.46(2) (1992) 151–165.], is obtained as a corollary. As a new application, we prove that the Turaev genus is equal to the number k of dealternator crossings for any dealternator connected diagram

Geometric tools in Juan de Álava's stonecutting workshop

Stonemasonry of the Gothic vault in its totality is based upon geometry of the line, whereas classic stereotomy relies on the comprehensive knowledge of the surface and the highly sophisticated sides of the voussoirs necessary for its vaults. It is obvious that this leap in the art of construction was paralleled and accompanied by an extension of the horizons of geometry. In Spain, it was made possible thanks to the centuries-old tradition of stone building begun in the most remote medieval times and to the presence of outstanding architects or stonemasons such as Juan de Álava, whose professional work surpassed the established limits and provided the art of building with new instruments.

Optimizing Functional Network Representation of Multivariate Time Series

By combining complex network theory and data mining techniques, we provide objective criteria for optimization of the functional network representation of generic multivariate time series. In particular, we propose a method for the principled selection of the threshold value for functional network reconstruction from raw data, and for proper identification of the network's indicators that unveil the most discriminative information on the system for classification purposes. We illustrate our method by analysing networks of functional brain activity of healthy subjects, and patients suffering from Mild Cognitive Impairment, an intermediate stage between the expected cognitive decline of normal aging and the more pronounced decline of dementia. We discuss extensions of the scope of the proposed methodology to network engineering purposes, and to other data mining tasks.

Using modular neural networks to model self-consciousness and self-representation for artificial entities

Self-consciousness implies not only self or group recognition, but also real knowledge of one’s own identity. Self-consciousness is only possible if an individual is intelligent enough to formulate an abstract self-representation. Moreover, it necessarily entails the capability of referencing and using this elf-representation in connection with other cognitive features, such as inference, and the anticipation of the consequences of both one’s own and other individuals’ acts. In this paper, a cognitive architecture for self-consciousness is proposed. This cognitive architecture includes several modules: abstraction, self-representation, other individuals'representation, decision and action modules. It includes a learning process of self-representation by direct (self-experience based) and observational learning (based on the observation of other individuals). For model implementation a new approach is taken using Modular Artificial Neural Networks (MANN). For model testing, a virtual environment has been implemented. This virtual environment can be described as a holonic system or holarchy, meaning that it is composed of autonomous entities that behave both as a whole and as part of a greater whole. The system is composed of a certain number of holons interacting. These holons are equipped with cognitive features, such as sensory perception, and a simplified model of personality and self-representation. We explain holons’ cognitive architecture that enables dynamic self-representation. We analyse the effect of holon interaction, focusing on the evolution of the holon’s abstract self-representation. Finally, the results are explained and analysed and conclusions drawn.