Zehaztasun handiko artikulazioen malgutasun analisia.

[EU]Azken urteetan argi geratu da gizakiak aurrera egiteko ezinbestekoa duela zehaztasuna. Teknologia berriak geroz eta bideratuagoak daude produktuen tamaina ahalik eta gehien murrizten edota produktu handien perdoiak nanometroetara hurbiltzeko ahaleginetan. Hau lortzeko bidean ezinbestekoa da elementu guztietan zehaztasuna limitera eramatea eta funtsean, honetan zentratuko da lan hau. Proiektu hau artikulazioen zehaztasuna hobetzeko tekniketan zentratuko da, gehiago zehaztuz, optika arloan lan egingo duen errobot baten artikulazioak analizatuko ditu. Artikulazioen zehaztasun optimoa lortzeko artikulazio hauek generazio berriko artikulazioak izatea pentsatu da, artikulazio flexible edo “flexible joints” izenekoak. Artikulazio hauek, orain artekoak ez bezala, ez dituzte bi elementu elkartuko, elementu bakarrez osatuta egongo dira eta bere buruarekiko errotazioz eta flexioz egingo dute lan honela, ohiko artikulazioek funtzionamendu egokirako behar duten lasaiera baztertu egingo da zehaztasun hobeak lortuz. Lan honetan zehar artikulazio flexible mota bat aukeratuko da eta geometriaren hainbat parametroren eta material ezberdinen aurrean edukiko duen jokaera analizatuko da. Aipatu beharra dago, artikulazio flexibleak azken hamarkadetan garatutako ideiak direnez beraiei buruzko informazioa oso pribatizatua dagoela eta ez dela lan erraza hau interneten edota liburutegietan topatzea. Ala ere, hauen analisirako aurkitu den informazio guztia eranskinetan dauden artikuluetan dago. Bertatik atera den informazio garrantzitsuena elementu finituen bitartezko analisian geometriak eduki beharreko baldintza batzuk eta ulermen eta aldaratze egokia lortzeko komeni diren datuak zehaztea izan da. Interesgarria da aipatzea analisiaren ondorioak konstante elastiko eta biratu dezaketen angelu maximoaren bitartez egin direla.

Choice of Flexible Production Technologies Under Strategic Delegation

This work analyzes a managerial delegation model in which firms can choose between a flexible production technology which allows them to produce two different products and a dedicated production technology which limits production to only one product. We analyze whether the incentives to adopt the flexible technology are smaller or greater in a managerial delegation model than under strict profit maximization. We obtain that the asymmetric equilibrium in which only one firm adopts the flexible technology can be sustained under strategic delegation but not under strict profit maximization when products are substitutes. We extend the analysis to consider welfare implications.

Cost-Saving production technologies and strategic delegation

This work analyzes a managerial delegation model in which firms that produce a differentiated good can choose between two production technologies: a low marginal cost technology and a high marginal cost technology. For the former to be adopted more investment is needed than for the latter. By giving managers of firms an incentive scheme based on a linear combination of profit and sales revenue, we find that Bertrand competition provides a stronger incentive to adopt the cost-saving technology than the strict profit maximization case. However, the results may be reversed under Cournot competition. We show that if the degree of product substitutability is sufficiently low (high), the incentive to adopt the cost-saving technology is larger under strict profit maximization (strategic delegation).

High-Throughput Sequencing of microRNAs in Peripheral Blood Mononuclear Cells: Identification of Potential Weight Loss Biomarkers

INTRODUCTION: MicroRNAs (miRNAs) are being increasingly studied in relation to energy metabolism and body composition homeostasis. Indeed, the quantitative analysis of miRNAs expression in different adiposity conditions may contribute to understand the intimate mechanisms participating in body weight control and to find new biomarkers with diagnostic or prognostic value in obesity management. OBJECTIVE: The aim of this study was the search for miRNAs in blood cells whose expression could be used as prognostic biomarkers of weight loss. METHODS: Ten Caucasian obese women were selected among the participants in a weight-loss trial that consisted in following an energy-restricted treatment. Weight loss was considered unsuccessful when <5% of initial body weight (non-responders) and successful when >5% (responders). At baseline, total miRNA isolated from peripheral blood mononuclear cells (PBMC) was sequenced with SOLiD v4. The miRNA sequencing data were validated by RT-PCR. RESULTS: Differential baseline expression of several miRNAs was found between responders and non-responders. Two miRNAs were up-regulated in the non-responder group (mir-935 and mir-4772) and three others were down-regulated (mir-223, mir-224 and mir-376b). Both mir-935 and mir-4772 showed relevant associations with the magnitude of weight loss, although the expression of other transcripts (mir-874, mir-199b, mir-766, mir-589 and mir-148b) also correlated with weight loss. CONCLUSIONS: This research addresses the use of high-throughput sequencing technologies in the search for miRNA expression biomarkers in obesity, by determining the miRNA transcriptome of PBMC. Basal expression of different miRNAs, particularly mir-935 and mir-4772, could be prognostic biomarkers and may forecast the response to a hypocaloric diet.

SNP Discovery in European Anchovy (Engraulis encrasicolus, L) by High-Throughput Transcriptome and Genome Sequencing

12 p.

ICGE: an R package for detecting relevant clusters and atypical units in gene expression

Background: Gene expression technologies have opened up new ways to diagnose and treat cancer and other diseases. Clustering algorithms are a useful approach with which to analyze genome expression data. They attempt to partition the genes into groups exhibiting similar patterns of variation in expression level. An important problem associated with gene classification is to discern whether the clustering process can find a relevant partition as well as the identification of new genes classes. There are two key aspects to classification: the estimation of the number of clusters, and the decision as to whether a new unit (gene, tumor sample ... ) belongs to one of these previously identified clusters or to a new group. Results: ICGE is a user-friendly R package which provides many functions related to this problem: identify the number of clusters using mixed variables, usually found by applied biomedical researchers; detect whether the data have a cluster structure; identify whether a new unit belongs to one of the pre-identified clusters or to a novel group, and classify new units into the corresponding cluster. The functions in the ICGE package are accompanied by help files and easy examples to facilitate its use. Conclusions: We demonstrate the utility of ICGE by analyzing simulated and real data sets. The results show that ICGE could be very useful to a broad research community.

Evaluation of two alternative carbon capture and storage technologies

4 p.

Evaluation of Two Alternative Carbon Capture and Storage Technologies: A Stochastic Model

30 p.

Complex systems in quantum technologies

124 p.

Contributions to learning Bayesian network models from weakly supervised data: Application to Assisted Reproductive Technologies and Software Defect Classification

162 p.

Design and implementation of a cloud computing adoption decision tool: Generating a cloud road

Migrating to cloud computing is one of the current enterprise challenges. This technology provides a new paradigm based on "on-demand payment" for information and communication technologies. In this sense, the small and medium enterprise is supposed to be the most interested, since initial investments are avoided and the technology allows gradual implementation. However, even if the characteristics and capacities have been widely discussed, entry into the cloud is still lacking in terms of practical, real frameworks. This paper aims at filling this gap, presenting a real tool already implemented and tested, which can be used as a cloud computing adoption decision tool. This tool uses diagnosis based on specific questions to gather the required information and subsequently provide the user with valuable information to deploy the business within the cloud, specifically in the form of Software as a Service (SaaS) solutions. This information allows the decision makers to generate their particular Cloud Road. A pilot study has been carried out with enterprises at a local level with a two-fold objective: To ascertain the degree of knowledge on cloud computing and to identify the most interesting business areas and their related tools for this technology. As expected, the results show high interest and low knowledge on this subject and the tool presented aims to readdress this mismatch, insofar as possible. Copyright: © 2015 Bildosola et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Ultrastrong light-matter interaction in quantum technologies

120 p.

Modelling and Simulation of ERTMS for Current and Future Mobile Technologies

Nowadays, train control in-lab simulation tools play a crucial role in reducing extensive and expensive on-site railway testing activities. In this paper, we present our contribution in this arena by detailing the internals of our European Railway Train Management System in-lab demonstrator. This demonstrator is built over a general-purpose simulation framework, Riverbed Modeler, previously Opnet Modeler. Our framework models both ERTMS subsystems, the Automatic Train Protection application layer based on movement authority message exchange and the telecommunication subsystem based on GSM-R communication technology. We provide detailed information on our modelling strategy. We also validate our simulation framework with real trace data. To conclude, under current industry migration scenario from GSM-R legacy obsolescence to IP-based heterogeneous technologies, our simulation framework represents a singular tool to railway operators. As an example, we present the assessment of related performance indicators for a specific railway network using a candidate replacement technology, LTE, versus current legacy technology. To the best of our knowledge, there is no similar initiative able to measure the impact of the telecommunication subsystem in the railway network availability.

Analysis of channel quality reporting mechanisms and their impact into 4G and beyond technologies

206 p.

Effects of Spring Temperatures on the Strength of Selection on Timing of Reproduction in a Long-Distance Migratory Bird

Climate change has differentially affected the timing of seasonal events for interacting trophic levels, and this has often led to increased selection on seasonal timing. Yet, the environmental variables driving this selection have rarely been identified, limiting our ability to predict future ecological impacts of climate change. Using a dataset spanning 31 years from a natural population of pied flycatchers (Ficedula hypoleuca), we show that directional selection on timing of reproduction intensified in the first two decades (1980-2000) but weakened during the last decade (2001-2010). Against expectation, this pattern could not be explained by the temporal variation in the phenological mismatch with food abundance. We therefore explored an alternative hypothesis that selection on timing was affected by conditions individuals experience when arriving in spring at the breeding grounds: arriving early in cold conditions may reduce survival. First, we show that in female recruits, spring arrival date in the first breeding year correlates positively with hatch date; hence, early-hatched individuals experience colder conditions at arrival than late-hatched individuals. Second, we show that when temperatures at arrival in the recruitment year were high, early-hatched young had a higher recruitment probability than when temperatures were low. We interpret this as a potential cost of arriving early in colder years, and climate warming may have reduced this cost. We thus show that higher temperatures in the arrival year of recruits were associated with stronger selection for early reproduction in the years these birds were born. As arrival temperatures in the beginning of the study increased, but recently declined again, directional selection on timing of reproduction showed a nonlinear change. We demonstrate that environmental conditions with a lag of up to two years can alter selection on phenological traits in natural populations, something that has important implications for our understanding of how climate can alter patterns of selection in natural populations.