Reconstruction of spatiotemporal capture data by means of orthogonal functions: the case of skipjack tuna (Katsuwonus pelamis) in the central-east Atlantic

[EN] The information provided by the International Commission for the Conservation of Atlantic Tunas (ICCAT) on captures of skipjack tuna (Katsuwonus pelamis) in the central-east Atlantic has a number of limitations, such as gaps in the statistics for certain fleets and the level of spatiotemporal detail at which catches are reported. As a result, the quality of these data and their effectiveness for providing management advice is limited. In order to reconstruct missing spatiotemporal data of catches, the present study uses Data INterpolating Empirical Orthogonal Functions (DINEOF), a technique for missing data reconstruction, applied here for the first time to fisheries data. DINEOF is based on an Empirical Orthogonal Functions decomposition performed with a Lanczos method. DINEOF was tested with different amounts of missing data, intentionally removing values from 3.4% to 95.2% of data loss, and then compared with the same data set with no missing data. These validation analyses show that DINEOF is a reliable methodological approach of data reconstruction for the purposes of fishery management advice, even when the amount of missing data is very high.

Impedance functions of end-bearing inclined piles.

[EN]In this work, stiffness and damping functions of pile foundations with inclined end-bearing piles have been computed for square 2X2 and 3X3 pile groups embedded in a soft stratum overlaying a rigid bedrock. The paper algo invetigates the influence that the assumption of a perfectly rigid bedrock and fixed boundary conditions at the pile tips have on the impedance functions.

Duality in complex stochastic boolean systems

[EN]Many different complex systems depend on a large number n of mutually independent random Boolean variables. The most useful representation for these systems –usually called complex stochastic Boolean systems (CSBSs)– is the intrinsic order graph. This is a directed graph on 2n vertices, corresponding to the 2n binary n-tuples (u1, . . . , un) ∈ {0, 1} n of 0s and 1s. In this paper, different duality properties of the intrinsic order graph are rigorously analyzed in detail. The results can be applied to many CSBSs arising from any scientific, technical or social area…

Complex stochastic boolean systems: comparing bitstrings with the same hamming weight

[EN]A complex stochastic Boolean system (CSBS) is a complex system depending on an arbitrarily large number

Complex sochastic boolean systems : new properties of the intrinsic order graph

[EN]A complex stochastic Boolean system (CSBS) is a system depending on an arbitrary number n of stochastic Boolean variables. The analysis of CSBSs is mainly based on the intrinsic order: a partial order relation defined on the set f0; 1gn of binary n-tuples. The usual graphical representation for a CSBS is the intrinsic order graph: the Hasse diagram of the intrinsic order. In this paper, some new properties of the intrinsic order graph are studied. Particularly, the set and the number of its edges, the degree and neighbors of each vertex, as well as typical properties, such as the symmetry and fractal structure of this graph, are analyzed…