Biomimetic Cloning of Quantum Observables

We propose a bio-inspired sequential quantum protocol for the cloning and preservation of the statistics associated to quantum observables of a given system. It combines the cloning of a set of commuting observables, permitted by the no-cloning and no-broadcasting theorems, with a controllable propagation of the initial state coherences to the subsequent generations. The protocol mimics the scenario in which an individual in an unknown quantum state copies and propagates its quantum information into an environment of blank qubits Finally, we propose a realistic experimental implementation of this protocol in trapped ions.

Reference Points Based on Dynamic Optimisation: A Versatil Algorithm for Mixed Fishery Management with Bio-economic Agestructured Models

Single-species management objectives may not be consistent within mixed fisheries. They may lead species to unsafe situations, promote discarding of over-quota and/or misreporting of catches. We provide an algorithm for characterising bio-economic reference points for a mixed fishery as the steady-state solution of a dynamic optimal management problem. The optimisation problem takes into account: i) that species are fishing simultaneously in unselective fishing operations and ii)intertemporal discounting and fleet costs to relate reference points to discounted economic profits along optimal trajectories. We illustrate how the algorithm can be implemented by applying it to the European Northern Stock of Hake (Merluccius merluccius), where fleets also capture Northern megrim (Lepidorhombus whiffiagonis) and Northern anglerfish (Lophius piscatorius and Lophius budegassa). We find that optimal mixed management leads to a target reference point that is quite similar to the 2/3 of the Fmsy single-species (hake) target. Mixed management is superior to singlespecies management because it leads the fishery to higher discounted profits with higher long-term SSB for all species. We calculate that the losses due to the use of the Fmsy single-species (hake) target in this mixed fishery account for 11.4% of total discounted profits.

Biologically-inspired data decorrelation for hyper-spectral imaging

Hyper-spectral data allows the construction of more robust statistical models to sample the material properties than the standard tri-chromatic color representation. However, because of the large dimensionality and complexity of the hyper-spectral data, the extraction of robust features (image descriptors) is not a trivial issue. Thus, to facilitate efficient feature extraction, decorrelation techniques are commonly applied to reduce the dimensionality of the hyper-spectral data with the aim of generating compact and highly discriminative image descriptors. Current methodologies for data decorrelation such as principal component analysis (PCA), linear discriminant analysis (LDA), wavelet decomposition (WD), or band selection methods require complex and subjective training procedures and in addition the compressed spectral information is not directly related to the physical (spectral) characteristics associated with the analyzed materials. The major objective of this article is to introduce and evaluate a new data decorrelation methodology using an approach that closely emulates the human vision. The proposed data decorrelation scheme has been employed to optimally minimize the amount of redundant information contained in the highly correlated hyper-spectral bands and has been comprehensively evaluated in the context of non-ferrous material classification

Valoración de bio-oil completo por craqueo catalítico en condiciones de la unidad FCC de refinería

351 p.

Poly(lactic acid)-based bio-blends and nanocomposites

172 p.

Pseudomona sp-ren bidez kate ertaineko gantz azidoen esterasa ekoizteko bio-erreaktore baten operazio baldintzen eta zinetikaren azterketa

[EUS] Proiektu honen helburua esterasaren lorpena aztertzeaz gain, lorpenerako erabilitako Pseudomona putida mikroorganismoaren hartzidura aztertzea da, ondoren mikroorganismo horri dagokion parametro zinetikoak lortzeko eta erreaktore baten diseinua egin ahal izateko. Horrekin batera, hartziduran eragin dezaketen faktoreak aztertuko dira (tenperatura, aparra, aireztapena, pH …) kontrol eta monitoriazioan kontutan izateko. Horrez guztiaz gain eta prozesua erreaktorean aztertzeaz gain, matrazeetan ere aztertu da, ondoren bi sistemetako hazkuntzak konparatzeko eta aztertzeko helburuarekin. Hartzidura prozesuaren ostean, esterasa proteina lorpena mintzen bidezko prozesuetan oinarrituko da. Proiektu honetan mintzak duten eraginkortasuna kalkulatuko da, baita lortutako emaitzen inguruko hausnarketa bat egin ere.

Sensing parasites: proteomic and advanced bio-detection alternatives

[EN] Parasitic diseases have a great impact in human and animal health. The gold standard for the diagnosis of the majority of parasitic infections is still conventional microscopy, which presents important limitations in terms of sensitivity and specificity and commonly requires highly trained technicians. More accurate molecular-based diagnostic tools are needed for the implementation of early detection, effective treatments and massive screenings with high-throughput capacities. In this respect, sensitive and affordable devices could greatly impact on sustainable control programmes which exist against parasitic diseases, especially in low income settings. Proteomics and nanotechnology approaches are valuable tools for sensing pathogens and host alteration signatures within microfluidic detection platforms. These new devices might provide novel solutions to fight parasitic diseases. Newly described specific parasite derived products with immune-modulatory properties have been postulated as the best candidates for the early and accurate detection of parasitic infections as well as for the blockage of parasite development. This review provides the most recent methodological and technological advances with great potential for biosensing parasites in their hosts, showing the newest opportunities offered by modern “-omics” and platforms for parasite detection and control.