Estudio de la distribución ambiental de los hongos del género Scedosporium en el País Vasco. Identificación de especies por técnicas moleculares.

El complejo de especies Scedosporium/Pseudallescheria está compuesto por diferentes especies de hongos filamentosos. De las cinco más habituales y utilizadas en este estudio existen tres especies de patógenos oportunistas clínicamente importantes, S. apiospermum, S prolificans y S. aurantiacum, que generan scedosporiosis especialmente en individuos inmuncocomprometidos. El aumento del número de este tipo de pacientes en los últimos años está elevando la incidencia de los casos de scedoporiosis. Scedosporium spp. se encuentran frecuentemente en hábitats humanizados y con presencia de contaminación. En este trabajo, se ha realizado un estudio para determinar su presencia en algunos hábitats de la Comunidad Autónoma del País Vasco (CAPV) y conocer su distribución, empleando técnicas microbiológicas y moleculares. No se aisló ninguna cepa del género en las playas de la CAPV, mientras que si que se encontraron en parques urbanos, aislándose la mayor cantidad de cepas y variedad de especies del género en las muestras de Araba. Por otro lado, se identificaron las especies del género mediante PCR, encontrándose cepas de S. prolificans, S. aurantiacum, S. dehoogii y P. minutispora. Además, se comprobó que los primers disponibles S. apiospermum no permitían discriminarlo del resto de especies.

Online exercise for the design and simulation of PCR and PCR-RFLP experiments

[EN] Background: Polymerase Chain Reaction (PCR) and Restriction Fragment Length Polymorphism of PCR products (PCR-RFLP) are extensively used molecular biology techniques. An exercise for the design and simulation of PCR and PCR-RFLP experiments will be a useful educational tool. Findings: An online PCR and PCR-RFLP exercise has been create that requires users to find the target genes,compare them, design primers, search for restriction endonucleases, and finally to simulate the experiment. Each user of the service is randomly assigned a gene from Escherichia coli; to complete the exercise, users must design an experiment capable of distinguishing among E. coli strains. By applying the experimental procedure to all completely sequenced E. coli, a basic understanding of strain comparison and clustering can also be acquired. Comparison of results obtained in different experiments is also very instructive. Conclusions: The exercise is freely available at http://insilico.ehu.es/edu.

A quantitative witness for Greenberger-Horne-Zeilinger entanglement

Along with the vast progress in experimental quantum technologies there is an increasing demand for the quantification of entanglement between three or more quantum systems. Theory still does not provide adequate tools for this purpose. The objective is, besides the quest for exact results, to develop operational methods that allow for efficient entanglement quantification. Here we put forward an analytical approach that serves both these goals. We provide a simple procedure to quantify Greenberger-Horne-Zeilinger-type multipartite entanglement in arbitrary three-qubit states. For two qubits this method is equivalent to Wootters' seminal result for the concurrence. It establishes a close link between entanglement quantification and entanglement detection by witnesses, and can be generalised both to higher dimensions and to more than three parties.

Efficient learning of decomposable models with a bounded clique size

The learning of probability distributions from data is a ubiquitous problem in the fields of Statistics and Artificial Intelligence. During the last decades several learning algorithms have been proposed to learn probability distributions based on decomposable models due to their advantageous theoretical properties. Some of these algorithms can be used to search for a maximum likelihood decomposable model with a given maximum clique size, k, which controls the complexity of the model. Unfortunately, the problem of learning a maximum likelihood decomposable model given a maximum clique size is NP-hard for k > 2. In this work, we propose a family of algorithms which approximates this problem with a computational complexity of O(k · n^2 log n) in the worst case, where n is the number of implied random variables. The structures of the decomposable models that solve the maximum likelihood problem are called maximal k-order decomposable graphs. Our proposals, called fractal trees, construct a sequence of maximal i-order decomposable graphs, for i = 2, ..., k, in k − 1 steps. At each step, the algorithms follow a divide-and-conquer strategy based on the particular features of this type of structures. Additionally, we propose a prune-and-graft procedure which transforms a maximal k-order decomposable graph into another one, increasing its likelihood. We have implemented two particular fractal tree algorithms called parallel fractal tree and sequential fractal tree. These algorithms can be considered a natural extension of Chow and Liu’s algorithm, from k = 2 to arbitrary values of k. Both algorithms have been compared against other efficient approaches in artificial and real domains, and they have shown a competitive behavior to deal with the maximum likelihood problem. Due to their low computational complexity they are especially recommended to deal with high dimensional domains.

The Forbidden Quantum Adder

Quantum information provides fundamentally different computational resources than classical information. We prove that there is no unitary protocol able to add unknown quantum states belonging to different Hilbert spaces. This is an inherent restriction of quantum physics that is related to the impossibility of copying an arbitrary quantum state, i.e., the no-cloning theorem. Moreover, we demonstrate that a quantum adder, in absence of an ancillary system, is also forbidden for a known orthonormal basis. This allows us to propose an approximate quantum adder that could be implemented in the lab. Finally, we discuss the distinct character of the forbidden quantum adder for quantum states and the allowed quantum adder for density matrices.

Diseño de la lógica programable de un sistema de monitorización de estructuras.

[ES]El objeto de este trabajo es desarrollar la lógica programable de una FPGA para un sistema de monitorización de estructuras. El diseño se compone de un generador de señales arbitrarias y un sistema de adquisición. El sistema de monitorización está dirigido al campo aeronáutico, pero se puede emplear en otras áreas.

Parity-dependent State Engineering and Tomography in the ultrastrong coupling regime

Reaching the strong coupling regime of light-matter interaction has led to an impressive development in fundamental quantum physics and applications to quantum information processing. Latests advances in different quantum technologies, like superconducting circuits or semiconductor quantum wells, show that the ultrastrong coupling regime (USC) can also be achieved, where novel physical phenomena and potential computational benefits have been predicted. Nevertheless, the lack of effective decoupling mechanism in this regime has so far hindered control and measurement processes. Here, we propose a method based on parity symmetry conservation that allows for the generation and reconstruction of arbitrary states in the ultrastrong coupling regime of light-matter interactions. Our protocol requires minimal external resources by making use of the coupling between the USC system and an ancillary two-level quantum system.

Identification of Sex and Female’s Reproductive Stage in Commercial Fish Species through the Quantification of Ribosomal Transcripts in Gonads

The estimation of maturity and sex of fish stocks in European waters is a requirement of the EU Data Collection Framework as part of the policy to improve fisheries management. On the other hand, research on fish biology is increasingly focused in molecular approaches, researchers needing correct identification of fish sex and reproductive stage without necessarily having in house the histological know-how necessary for the task. Taking advantage of the differential gene transcription occurring during fish sex differentiation and gametogenesis, the utility of 5S ribosomal RNA (5S rRNA) and General transcription factor IIIA (gtf3a) in the molecular identification of sex and gametogenic stage was tested in different economically-relevant fish species from the Bay of Biscay. Gonads of 9 fish species (, Atlantic, Atlantic-chub and horse mackerel, blue whiting, bogue, European anchovy, hake and pilchard and megrim), collected from local commercial fishing vessels were histologically sexed and 5S and 18S rRNA concentrations were quantified by capillary electrophoresis to calculate a 5S/18S rRNA index. Degenerate primers permitted cloning and sequencing of gtf3a fragments in 7 of the studied species. 5S rRNA and gtf3a transcript levels, together with 5S/18S rRNA index, distinguished clearly ovaries from testis in all of the studied species. The values were always higher in females than in males. 5S/18S rRNA index values in females were always highest when fish were captured in early phases of ovary development whilst, in later vitellogenic stages, the values decreased significantly. In megrim and European anchovy, where gonads in different oogenesis stages were obtained, the 5S/18S rRNA index identified clearly gametogenic stage. This approach, to the sexing and the quantitative non-subjective identification of the maturity stage of female fish, could have multiple applications in the study of fish stock dynamics, fish reproduction and fecundity and fish biology in general.