Semi-supervised subspace clustering and applications to neuroscience

Machine learning techniques are used for extracting valuable knowledge from data. Nowa¬days, these techniques are becoming even more important due to the evolution in data ac¬quisition and storage, which is leading to data with different characteristics that must be exploited. Therefore, advances in data collection must be accompanied with advances in machine learning techniques to solve new challenges that might arise, on both academic and real applications. There are several machine learning techniques depending on both data characteristics and purpose. Unsupervised classification or clustering is one of the most known techniques when data lack of supervision (unlabeled data) and the aim is to discover data groups (clusters) according to their similarity. On the other hand, supervised classification needs data with supervision (labeled data) and its aim is to make predictions about labels of new data. The presence of data labels is a very important characteristic that guides not only the learning task but also other related tasks such as validation. When only some of the available data are labeled whereas the others remain unlabeled (partially labeled data), neither clustering nor supervised classification can be used. This scenario, which is becoming common nowadays because of labeling process ignorance or cost, is tackled with semi-supervised learning techniques. This thesis focuses on the branch of semi-supervised learning closest to clustering, i.e., to discover clusters using available labels as support to guide and improve the clustering process. Another important data characteristic, different from the presence of data labels, is the relevance or not of data features. Data are characterized by features, but it is possible that not all of them are relevant, or equally relevant, for the learning process. A recent clustering tendency, related to data relevance and called subspace clustering, claims that different clusters might be described by different feature subsets. This differs from traditional solutions to data relevance problem, where a single feature subset (usually the complete set of original features) is found and used to perform the clustering process. The proximity of this work to clustering leads to the first goal of this thesis. As commented above, clustering validation is a difficult task due to the absence of data labels. Although there are many indices that can be used to assess the quality of clustering solutions, these validations depend on clustering algorithms and data characteristics. Hence, in the first goal three known clustering algorithms are used to cluster data with outliers and noise, to critically study how some of the most known validation indices behave. The main goal of this work is however to combine semi-supervised clustering with subspace clustering to obtain clustering solutions that can be correctly validated by using either known indices or expert opinions. Two different algorithms are proposed from different points of view to discover clusters characterized by different subspaces. For the first algorithm, available data labels are used for searching for subspaces firstly, before searching for clusters. This algorithm assigns each instance to only one cluster (hard clustering) and is based on mapping known labels to subspaces using supervised classification techniques. Subspaces are then used to find clusters using traditional clustering techniques. The second algorithm uses available data labels to search for subspaces and clusters at the same time in an iterative process. This algorithm assigns each instance to each cluster based on a membership probability (soft clustering) and is based on integrating known labels and the search for subspaces into a model-based clustering approach. The different proposals are tested using different real and synthetic databases, and comparisons to other methods are also included when appropriate. Finally, as an example of real and current application, different machine learning tech¬niques, including one of the proposals of this work (the most sophisticated one) are applied to a task of one of the most challenging biological problems nowadays, the human brain model¬ing. Specifically, expert neuroscientists do not agree with a neuron classification for the brain cortex, which makes impossible not only any modeling attempt but also the day-to-day work without a common way to name neurons. Therefore, machine learning techniques may help to get an accepted solution to this problem, which can be an important milestone for future research in neuroscience. Resumen Las técnicas de aprendizaje automático se usan para extraer información valiosa de datos. Hoy en día, la importancia de estas técnicas está siendo incluso mayor, debido a que la evolución en la adquisición y almacenamiento de datos está llevando a datos con diferentes características que deben ser explotadas. Por lo tanto, los avances en la recolección de datos deben ir ligados a avances en las técnicas de aprendizaje automático para resolver nuevos retos que pueden aparecer, tanto en aplicaciones académicas como reales. Existen varias técnicas de aprendizaje automático dependiendo de las características de los datos y del propósito. La clasificación no supervisada o clustering es una de las técnicas más conocidas cuando los datos carecen de supervisión (datos sin etiqueta), siendo el objetivo descubrir nuevos grupos (agrupaciones) dependiendo de la similitud de los datos. Por otra parte, la clasificación supervisada necesita datos con supervisión (datos etiquetados) y su objetivo es realizar predicciones sobre las etiquetas de nuevos datos. La presencia de las etiquetas es una característica muy importante que guía no solo el aprendizaje sino también otras tareas relacionadas como la validación. Cuando solo algunos de los datos disponibles están etiquetados, mientras que el resto permanece sin etiqueta (datos parcialmente etiquetados), ni el clustering ni la clasificación supervisada se pueden utilizar. Este escenario, que está llegando a ser común hoy en día debido a la ignorancia o el coste del proceso de etiquetado, es abordado utilizando técnicas de aprendizaje semi-supervisadas. Esta tesis trata la rama del aprendizaje semi-supervisado más cercana al clustering, es decir, descubrir agrupaciones utilizando las etiquetas disponibles como apoyo para guiar y mejorar el proceso de clustering. Otra característica importante de los datos, distinta de la presencia de etiquetas, es la relevancia o no de los atributos de los datos. Los datos se caracterizan por atributos, pero es posible que no todos ellos sean relevantes, o igualmente relevantes, para el proceso de aprendizaje. Una tendencia reciente en clustering, relacionada con la relevancia de los datos y llamada clustering en subespacios, afirma que agrupaciones diferentes pueden estar descritas por subconjuntos de atributos diferentes. Esto difiere de las soluciones tradicionales para el problema de la relevancia de los datos, en las que se busca un único subconjunto de atributos (normalmente el conjunto original de atributos) y se utiliza para realizar el proceso de clustering. La cercanía de este trabajo con el clustering lleva al primer objetivo de la tesis. Como se ha comentado previamente, la validación en clustering es una tarea difícil debido a la ausencia de etiquetas. Aunque existen muchos índices que pueden usarse para evaluar la calidad de las soluciones de clustering, estas validaciones dependen de los algoritmos de clustering utilizados y de las características de los datos. Por lo tanto, en el primer objetivo tres conocidos algoritmos se usan para agrupar datos con valores atípicos y ruido para estudiar de forma crítica cómo se comportan algunos de los índices de validación más conocidos. El objetivo principal de este trabajo sin embargo es combinar clustering semi-supervisado con clustering en subespacios para obtener soluciones de clustering que puedan ser validadas de forma correcta utilizando índices conocidos u opiniones expertas. Se proponen dos algoritmos desde dos puntos de vista diferentes para descubrir agrupaciones caracterizadas por diferentes subespacios. Para el primer algoritmo, las etiquetas disponibles se usan para bus¬car en primer lugar los subespacios antes de buscar las agrupaciones. Este algoritmo asigna cada instancia a un único cluster (hard clustering) y se basa en mapear las etiquetas cono-cidas a subespacios utilizando técnicas de clasificación supervisada. El segundo algoritmo utiliza las etiquetas disponibles para buscar de forma simultánea los subespacios y las agru¬paciones en un proceso iterativo. Este algoritmo asigna cada instancia a cada cluster con una probabilidad de pertenencia (soft clustering) y se basa en integrar las etiquetas conocidas y la búsqueda en subespacios dentro de clustering basado en modelos. Las propuestas son probadas utilizando diferentes bases de datos reales y sintéticas, incluyendo comparaciones con otros métodos cuando resulten apropiadas. Finalmente, a modo de ejemplo de una aplicación real y actual, se aplican diferentes técnicas de aprendizaje automático, incluyendo una de las propuestas de este trabajo (la más sofisticada) a una tarea de uno de los problemas biológicos más desafiantes hoy en día, el modelado del cerebro humano. Específicamente, expertos neurocientíficos no se ponen de acuerdo en una clasificación de neuronas para la corteza cerebral, lo que imposibilita no sólo cualquier intento de modelado sino también el trabajo del día a día al no tener una forma estándar de llamar a las neuronas. Por lo tanto, las técnicas de aprendizaje automático pueden ayudar a conseguir una solución aceptada para este problema, lo cual puede ser un importante hito para investigaciones futuras en neurociencia.

Conceptual design of the liquid metal laboratory of the TECHNOFUSION facility

The application of liquid metal technology in fusion devices requires R&D related to many phenomena: interaction between liquid metals and structural material as corrosion, erosion and passivation techniques; magneto-hydrodynamics; free surface fluid-dynamics and any other physical aspect that will be needed for their safe reliable operation. In particular, there is a significant shortage of experimental facilities dedicated to the development of the lithium technology. In the framework of the TECHNOFUSION project, an experimental laboratory devoted to the lithium technology development is proposed, in order to shed some light in the path to IFMIF and the design of chamber's first wall and divertors. The conceptual design foresee a development in two stages, the first one consisting on a material testing loop. The second stage proposes the construction of a mock-up of the IFMIF target that will allow to assess the behaviour of a free-surface lithium target under vacuum conditions. In this paper, such conceptual design is addressed.

Geochemical monitoring in the Hontomín (Burgos, Spain) injection site: preliminary results and perspectives

CO2 capture and storage (CCS) projects are presently developed to reduce the emission of anthropogenic CO2 into the atmosphere. CCS technologies are expected to account for the 20% of the CO2 reduction by 2050. One of the main concerns of CCS is whether CO2 may remain confined within the geological formation into which it is injected since post-injection CO2 migration in the time scale of years, decades and centuries is not well understood. Theoretically, CO2 can be retained at depth i) as a supercritical fluid (physical trapping), ii) as a fluid slowly migrating in an aquifer due to long flow path (hydrodynamic trapping), iii) dissolved into ground waters (solubility trapping) and iv) precipitated secondary carbonates. Carbon dioxide will be injected in the near future (2012) at Hontomín (Burgos, Spain) in the frame of the Compostilla EEPR project, led by the Fundación Ciudad de la Energía (CIUDEN). In order to detect leakage in the operational stage, a pre-injection geochemical baseline is presently being developed. In this work a geochemical monitoring design is presented to provide information about the feasibility of CO2 storage at depth.

Characterization of an 241AmBe neutron irradiation facility by different spectrometric techniques

An automated panoramic irradiator with a 3 Ci 241Am-Be neutron source is installed in a bunker-type large room at the Universidad Politécnica de Madrid (UPM). It was recently modified and a neutron spectrometry campaign was organized to characterize the neutron fields in different measurement points along the irradiation bench. Four research groups working with different Bonner Sphere Spectrometers (BSS) and using different spectral unfolding codes took part to this exercise. INFN-LNF used a BSS formed by 9 spheres plus bare detector, with cylindrical, almost point like, 6LiI(Eu) scintillator (4 mm x 4 mm, from Ludlum); UAZ-UPM employed a similar system but with only 6 spheres plus bare detector; UAB worked with a 3He filled proportional counter at 8kPa filling pressure, cylindrical 9 mm x 10 mm (05NH1 from Eurisys) with 11 spheres configuration; and CIEMAT used 12 spheres with an spherical 3He SP9 counter (Centronic Ltd., UK) with very high sensitivity due to the large diameter (3.2 cm) and the filling pressure of the order of 228 kPa. Each group applied a different spectral unfolding method: INFN and UAB worked with FRUIT ver. 3.0 with their own response matrixes; UAZ-UPM used the BUNKIUT unfolding code with the response matrix UTA4 and CIEMAT employed the GRAVEL-MAXED-IQU package with their own response matrix. The paper shows the main results obtained in terms of neutron spectra at fixed distances from the source as well as total neutron fluence rate and ambient dose equivalent rate H*(10) determined from the spectra. The latter are compared with the readings of a common active survey-meter (LB 6411). The small differences in the results of the various groups are discussed.

Hydrogeochemistry of surface and spring waters in the surroundings of the CO2 injection site at Hontomín–Huermeces (Burgos, Spain)

In this paper the very first geochemical and isotopic data related to surface and spring waters and dissolved gases in the area of Hontomín–Huermeces (Burgos, Spain) are presented and discussed. Hontomín–Huermeces has been selected as a pilot site for the injection of pure (>99%) CO2. Injection and monitoring wells are planned to be drilled close to 6 oil wells completed in the 1980s for which detailed stratigraphical logs are available, indicating the presence of a confined saline aquifer at the depth of about 1500 m into which less than 100,000 tons of iquid CO2 will be injected, possibly starting in 2013. The chemical and features of the spring waters suggest that they are related to a shallow hydrogeological system as the concentration of the Total Dissolved Solids approaches 800 mg/L with a Ca2+(Mg2+)-HCO3− composition, similar to that of the surface waters. This is also supported by the oxygen and hydrogen isotopic ratios that have values lying between those of the Global and the Mediterranean Meteoric Water Lines. Some spring waters close to the oil wells are haracterized by relatively high concentrations of NO3− (up to 123 mg/L), unequivocally suggesting an anthropogenic source that adds to the main water–rock interaction processes. The latter can be referred to Ca-Mg-carbonate and, at a minor extent, Al-silicate dissolution, being the outcropping sedimentary rocks characterized by Palaeozoic to Quaternary rocks. Anomalous concentrations of Cl−, SO42−, As, B and Ba were measured in two springs discharging a few hundred meters from the oil wells and in the Rio Ubierna. These contents are significantly higher than those of the whole set of the studied waters and are possibly indicative of mixing processes, although at very low extent, between deep and shallow aquifers. No evidence of deep-seated gases interacting with the Hontomín–Huermeces waters was recognized in the chemistry of the disolved gases. This is likely due to the fact that they are mainly characterized by an atmospheric source as highlighted by the high contents of N2, O2 and Ar and by N2/Ar ratios that approach that of ASW (Air Saturated Water) and possibly masking any contribution related to a deep source. Nevertheless, significant concentrations (up to 63% by vol.) of isotopically negative CO2 (<−17.7‰ V-PDB) were found in some water samples, likely related to a biogenic source. The geochemical and isotopic data of this work are of particular importance when a monitoring program will be established to verify whether CO2 leakages, induced by the injection of this greenhouse gas, may be affecting the quality of the waters in the shallow hydrological circuits at Hontomín–Huermeces. In this respect, carbonate chemistry, the isotopic carbon of dissolved CO2 and TDIC (Total Dissolved Inorganic Carbon) and selected trace elements can be considered as useful parameters to trace the migration of the injected CO2 into near-surface environments.

CO2 soil flux baseline at the technological development plant for CO2 injection at Hontomin (Burgos, Spain)

From the end of 2013 and during the following two years, 20 kt of CO2sc are planned to be injected in a saline reservoir (1500 m depth) at the Hontomín site (NE Spain). The target aquifers are Lower Jurassic limestone formations which are sealed by Lower Cretaceous clay units at the Hontomín site (NE Spain). The injection of CO2 is part of the activities committed in the Technology Development phase of the EC-funded OXYCFB300 project (European Energy Program for Recovery – EEPR, http://www.compostillaproject.eu), which include CO2 injection strategies, risk assessment, and testing and validating monitoring methodologies and techniques. Among the monitoring works, the project is intended to prove that present-day technology is able to monitor the evolution of injected CO2 in the reservoir and to detect potential leakage. One of the techniques is the measurement of CO2 flux at the soil–atmosphere interface, which includes campaigns before, during and after the injection operations. In this work soil CO2 flux measurements in the vicinity of oil borehole, drilled in the eighties and named H-1 to H-4, and injection and monitoring wells were performed using an accumulation chamber equipped with an IR sensor. Seven surveys were carried out from November 2009 to summer 2011. More than 4000 measurements were used to determine the baseline flux of CO2 and its seasonal variations. The measured values were low (from 5 to 13 g m−2 day−1) and few outliers were identified, mainly located close to the H-2 oil well. Nevertheless, these values cannot be associated to a deep source of CO2, being more likely related to biological processes, i.e. soil respiration. No anomalies were recognized close to the deep fault system (Ubierna Fault) detected by geophysical investigations. There, the CO2 flux is indeed as low as other measurement stations. CO2 fluxes appear to be controlled by the biological activity since the lowest values were recorded during autumn-winter seasons and they tend to increase in warm periods. Two reference CO2 flux values (UCL50 of 5 g m−2 d−1 for non-ploughed areas in autumn–winter seasons and 3.5 and 12 g m−2 d−1 for in ploughed and non-ploughed areas, respectively, in spring–summer time, and UCL99 of 26 g m−2 d−1 for autumn–winter in not-ploughed areas and 34 and 42 g m−2 d−1 for spring–summer in ploughed and not-ploughed areas, respectively) were calculated. Fluxes higher than these reference values could be indicative of possible leakage during the operational and post-closure stages of the storage project.

Adaptive neuro-fuzzy inference systems (ANFIS) for supervised classification of competence in MIS based on psychomotor skills

INTRODUCTION: Objective assessment of motor skills has become an important challenge in minimally invasive surgery (MIS) training.Currently, there is no gold standard defining and determining the residents' surgical competence.To aid in the decision process, we analyze the validity of a supervised classifier to determine the degree of MIS competence based on assessment of psychomotor skills METHODOLOGY: The ANFIS is trained to classify performance in a box trainer peg transfer task performed by two groups (expert/non expert). There were 42 participants included in the study: the non-expert group consisted of 16 medical students and 8 residents (< 10 MIS procedures performed), whereas the expert group consisted of 14 residents (> 10 MIS procedures performed) and 4 experienced surgeons. Instrument movements were captured by means of the Endoscopic Video Analysis (EVA) tracking system. Nine motion analysis parameters (MAPs) were analyzed, including time, path length, depth, average speed, average acceleration, economy of area, economy of volume, idle time and motion smoothness. Data reduction was performed by means of principal component analysis, and then used to train the ANFIS net. Performance was measured by leave one out cross validation. RESULTS: The ANFIS presented an accuracy of 80.95%, where 13 experts and 21 non-experts were correctly classified. Total root mean square error was 0.88, while the area under the classifiers' ROC curve (AUC) was measured at 0.81. DISCUSSION: We have shown the usefulness of ANFIS for classification of MIS competence in a simple box trainer exercise. The main advantage of using ANFIS resides in its continuous output, which allows fine discrimination of surgical competence. There are, however, challenges that must be taken into account when considering use of ANFIS (e.g. training time, architecture modeling). Despite this, we have shown discriminative power of ANFIS for a low-difficulty box trainer task, regardless of the individual significances between MAPs. Future studies are required to confirm the findings, inclusion of new tasks, conditions and sample population.

Water chemistry at Hontomín-Huermeces (Burgos, Spain): insights for a pre-, intra- and post-CO2 injection geochemical monitoring.

In this study, the very first geochemical and isotopic data related to surface and spring waters and dissolved gases in the area of Hontomín-Huermeces (Burgos, Spain) are presented and discussed. Hontomín-Huermeces was selected as a pilot site for the injection of pure (>99 %) CO2. Injection and monitoring wells are planned to be drilled close to 6 oil wells completed in the 1980’s. Stratigraphical logs indicate the presence of a confined saline aquifer at the depth of about 1,500 m into which less than 100,000 tons of liquid CO2 will be injected, possibly starting in 2013. The chemical and isotopic features of the spring waters suggest the occurrence of a shallow aquifer having a Ca2+(Mg2+)-HCO3- composition, relatively low salinity (Total Dissolved Solids _800 mg/L) and a meteoric isotopic signature. Some spring waters close to the oil wells are characterized by relatively high concentrations of NO3- (up to 123 mg/L), unequivocally indicating anthropogenic contamination that adds to the main water-rock interaction processes. The latter can be referred to Ca-Mg-carbonate and, at a minor extent, Al-silicate dissolution, being the outcropping sedimentary rocks characterized by Palaeozoic to Quaternary rocks. Anomalous concentrations of Cl-, SO42-, As, B and Ba were measured in two springs discharging a few hundreds meters from the oil wells and in the Rio Ubierna, possibly indicative of mixing processes, although at very low extent, between deep and shallow aquifers. Gases dissolved in spring waters show relatively high concentrations of atmospheric species, such as N2, O2 and Ar, and isotopically negative CO2 (<-17.7 h V-PDB), likely related to a biogenic source, possibly masking any contribution related to a deep source. The geochemical and isotopic data of this study are of particular importance when a monitoring program will be established to verify whether CO2 leakages, induced by the injection of this greenhouse gas, may affect the quality of the waters of the shallow Hontomín-Huermeces hydrological circuit. In this respect, carbonate chemistry, the isotopic carbon of dissolved CO2 and TDIC (Total Dissolved Inorganic Carbon) and selected trace elements can be considered as useful parameters to trace the migration of the injected CO2 into near-surface environments.

The facility manager architect : the social responsability as an added value.

From the very first steps to execute a building, it is essential to analyze its life cycle. Similarly, we should consider the life cycle when projecting an urban intervention. Professionals of the Facility Management take part in construction projects, developing and managing DBFMO projects (Design, Build, Finance, Maintenance & Operate). Whatever the nature of the promoter is – private or public – promoters are leaders in projects of responsible management of spaces, whether these are work spaces, leisure spaces or residential spaces. They know and identify with the company and its performance, its values and its needs. These professionals give sustainable solutions in the life cycle of buildings (offices and housing), new ways to work and initiatives of innovations linked to current social changes: technology, social networks, and new habits. Concepts where innovation is essential should consider responsible values. Social, economic and sustainable aspects have to associate with the management performed by a Facilities Manager when considering the three groups of stakeholders with which it is linked: economic (shareholders), contractual (users), non-contractual (neighborhoods, organizations, etc.). Marcus Vitruvius Pollio, at the beginning of his book "The Ten Books on Architecture" describes and argues how the distribution in buildings must always adapt to their inhabitants. Let us build cities and buildings with responsible criteria, bearing in mind all its users and the needs of each one of them. Not to mention the need to adapt to future requirements with minimum cost and maximum profitability. These needs, under responsible management, are competencies developed by a Facilities Manager in his day to day. He cares and takes over the entire life cycle of buildings and their surroundings. This work is part of the PhD project whose main aim is to study the added value to the architectural profession when social responsibility criteria are applied in his/her role as Facility Manager.

People and Facility Management. The team: the main asset of any management

From the moment we enter a large office building until we leave it, we receive a lot of attentions served by the management of services to the user. However, it is usually quite inappreciable the work that is being developed to keep things running smoothly.The services provided in a building are carried out by people. However, we often tend to forget these people when we talk about the tasks that make that a building operates properly 24 hours a day, 365 days a year.But, for example, what would happen if one day the service provided by the reception in a large building did not function as it should? What would it be like if one day the person performing the service of maintenance of the building's cleaning were not at his post? How would the working day develop if there were not a correct air handling system?People are the foundation of the proper functioning of a building. The work of the Facilities Manager and the Facility Management is the management of their functions: the responsible management of the team.

Conceptual design of the beryllium rotating target for the ESS-Bilbao facility

The ESS-Bilbao facility, hosted by the University of the Basque Country (UPV/EHU), envisages the operation of a high-current proton accelerator delivering beams with energies up to 50 MeV. The time-averaged proton current will be 2.25 mA, delivered by 1.5 ms proton pulses with a repetition rate of 20 Hz. This beam will feed a neutron source based upon the Be (p,n) reaction, which will enable the provision of relevant neutron experimentation capabilities. The neutron source baseline concept consists in a rotating beryllium target cooled by water. The target structure will comprise a rotatable disk made of 6061-T6 aluminium alloy holding 20 beryllium plates. Heat dissipation from the target relies upon a distribution of coolant-flow channels. The practical implementation of such a concept is here described with emphasis put on the beryllium plates thermo-mechanical optimization, the chosen coolant distribution system as well as the mechanical behavior of the assembly.

Supervised classification of minimally invasive surgery psychomotor competence based on instruments motion analysis

Background Objective assessment of psychomotor skills has become an important challenge in the training of minimally invasive surgical (MIS) techniques. Currently, no gold standard defining surgical competence exists for classifying residents according to their surgical skills. Supervised classification has been proposed as a means for objectively establishing competence thresholds in psychomotor skills evaluation. This report presents a study comparing three classification methods for establishing their validity in a set of tasks for basic skills’ assessment. Methods Linear discriminant analysis (LDA), support vector machines (SVM), and adaptive neuro-fuzzy inference systems (ANFIS) were used. A total of 42 participants, divided into an experienced group (4 expert surgeons and 14 residents with >10 laparoscopic surgeries performed) and a nonexperienced group (16 students and 8 residents with <10 laparoscopic surgeries performed), performed three box trainer tasks validated for assessment of MIS psychomotor skills. Instrument movements were captured using the TrEndo tracking system, and nine motion analysis parameters (MAPs) were analyzed. The performance of the classifiers was measured by leave-one-out cross-validation using the scores obtained by the participants. Results The mean accuracy performances of the classifiers were 71 % (LDA), 78.2 % (SVM), and 71.7 % (ANFIS). No statistically significant differences in the performance were identified between the classifiers. Conclusions The three proposed classifiers showed good performance in the discrimination of skills, especially when information from all MAPs and tasks combined were considered. A correlation between the surgeons’ previous experience and their execution of the tasks could be ascertained from results. However, misclassifications across all the classifiers could imply the existence of other factors influencing psychomotor competence.

High-frequency signal generation using 1550 nm VCSEL subject to two-frequency optical injection

We experimentally investigate high-frequency microwave signal generation using a 1550 nm single-mode VCSEL subject to two-frequency optical injection. We first consider a situation in which the injected signals come from two similar VCSELs. The polarization of the injected light is parallel to that of the injected VCSEL. We obtain that the VCSEL can be locked to one of the injected signals, but the observed microwave signal is originated by beating at the photodetector. In a second situation we consider injected signals that come from two external cavity tunable lasers with a significant increase of the injected power with respect to the VCSEL-by-VCSEL injection case. The polarization of the injected light is orthogonal to that of the free-running slave VCSEL. We show that in this case it is possible to generate a microwave signal inside the VCSEL cavity. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Adaptaciones cardiacas hemodinámicas, estructurales y funcionales a un programa de ejercicio físico supervisado durante el embarazo: ensayo clínico aleatorizado = Hemodynamic, structural and functional cardiac adaptations in a supervised physical exercise program during pregnancy: a randomized controlled trial

Introducción: Diversos cambios ocurren en el sistema cardiovascular materno durante el embarazo, lo que genera un gran estrés sobre este sistema especialmente durante el tercer trimestre, pudiendo acentuarse en presencia de determinados factores de riesgo. Los objetivos de este estudio fueron, valorar las adaptaciones cardiovasculares producidas por un programa específico de ejercicio físico; su seguridad sobre el sistema cardiovascular materno y los resultados del embarazo; y su eficacia en el control de los factores de riesgo cardiovascular. Material y métodos: El diseño del estudio fue un ensayo clínico aleatorizado. 151 gestantes sanas fueron evaluadas mediante un ecocardiograma y un electrocardiograma en la semana 20 y 34 de gestación. Un total de 89 gestantes participaron en un programa de ejercicio físico (GE) desde el primer hasta el tercer trimestre de embarazo, constituido principalmente por 25-30 minutos de trabajo aeróbico (55-60% de la frecuencia cardiaca de reserva), trabajo de fortalecimiento general y específico, y un trabajo de tonificación del suelo pélvico; desarrollado 3 días a la semana con una duración de 55-60 minutos cada sesión. Las gestantes aleatoriamente asignadas al grupo de control (GC; n=62) permanecieron sedentarias durante el embarazo. El estudio fue aprobado por el Comité Ético de investigación clínica del Hospital Universitario de Fuenlabrada. Resultados: Las características basales fueron similares entre ambos grupos. A diferencia del GC, las gestantes del GE evitaron el descenso significativo del gasto cardiaco indexado, entre el 2º y 3ºT de embarazo, y conservaron el patrón geométrico normal del ventrículo izquierdo; mientras que en el GC cambió hacia un patrón de remodelado concéntrico. En la semana 20, las gestantes del GE presentaron valores significativamente menores de frecuencia cardiaca (GC: 79,56±10,76 vs. GE: 76,05±9,34; p=0,04), tensión arterial sistólica (GC: 110,19±10,23 vs. GE: 106,04±12,06; p=0,03); tensión arterial diastólica (GC: 64,56±7,88 vs. GE: 61,81±7,15; p=0,03); tiempo de relajación isovolumétrica (GC: 72,94±14,71 vs. GE: 67,05±16,48; p=0,04); y un mayor tiempo de deceleración de la onda E (GC: 142,09±39,11 vs. GE: 162,10±48,59; p=0,01). En la semana 34, el GE presentó valores significativamente superiores de volumen sistólico (GC: 51,13±11,85 vs. GE: 56,21±12,79 p=0,04), de llenado temprano del ventrículo izquierdo (E) (GC: 78,38±14,07 vs. GE: 85,30±16,62; p=0,02) y de tiempo de deceleración de la onda E (GC: 130,35±37,11 vs. GE: 146,61±43,40; p=0,04). Conclusión: La práctica regular de ejercicio físico durante el embarazo puede producir adaptaciones positivas sobre el sistema cardiovascular materno durante el tercer trimestre de embarazo, además de ayudar en el control de sus factores de riesgo, sin alterar la salud materno-fetal. ABSTRACT Background: Several changes occur in the maternal cardiovascular system during pregnancy. These changes produce a considerable stress in this system, especially during the third trimester, which can be increased in presence of some risk factors. The aims of this study were, to assess the maternal cardiac adaptations in a specific exercise program; its safety on the maternal cardiovascular system and pregnancy outcomes; and its effectiveness in the control of cardiovascular risk factors. Material and methods: A randomized controlled trial was designed. 151 healthy pregnant women were assessed by an echocardiography and electrocardiography at 20 and 34 weeks of gestation. A total of 89 pregnant women participated in a physical exercise program (EG) from the first to the third trimester of pregnancy. It consisted of 25-30 minutes of aerobic conditioning (55-60% of their heart rate reserve), general and specific strength exercises, and a pelvic floor muscles training; 3 times per weeks during 55-60 minutes per session. Pregnant women randomized allocated to the control group (CG) remained sedentary during pregnancy. The study was approved by the Research Ethics Committee of Hospital Universitario de Fuenlabrada. Results: Baseline characteristics were similar between groups. Difference from the CG, pregnant women from the EG prevented the significant decrease of the cardiac output index, between the 2nd and 3rd trimester of pregnancy, and preserved the normal left ventricular pattern; whereas in the CG shifted to concentric remodeling pattern. At 20 weeks, women in the EG had significant lower heart rate (CG: 79,56±10,76 vs. EG: 76,05±9,34; p=0,04), systolic blood pressure (CG: 110,19±10,23 vs. EG: 106,04±12,06; p=0,03); diastolic blood pressure (CG: 64,56±7,88 vs. EG: 61,81±7,15; p=0,03); isovolumetric relaxation time (GC: 72,94±14,71 vs. GE: 67,05±16,48; p=0,04); and a higher deceleration time of E Wave (GC: 142,09±39,11 vs. GE: 162,10±48,59; p=0,01). At 34 weeks, the EG had a significant higher stroke volume (CG: 51,13±11,85 vs. EG: 56,21±12,79 p=0,04), early filling of left ventricular (E) (CG: 78,38±14,07 vs. EG: 85,30±16,62; p=0,02) and deceleration time of E wave (CG: 130,35±37,11 vs. EG:146,61±43,40; p=0,04). Conclusion: Physical regular exercise program during pregnancy may produce positive maternal cardiovascular adaptations during the third trimester of pregnancy. In addition, it helps to control the cardiovascular risk factors without altering maternal and fetus health.

Design, development and construction of an outdoor testing facility for semi-transparent photovoltaic modules

Building-integrated Photovoltaics (BIPV) is one of the most promising technologies enabling buildings to generate on-site part of their electricity needs while performing architectural functionalities. A clear example of BIPV products consists of semi-transparent photovoltaic modules (STPV), designed to replace the conventional glazing solutions in building façades. Accordingly, the active building envelope is required to perform multiple requirements such as provide solar shading to avoid overheating, supply solar gains and thermal insulation to reduce heat loads and improve daylight utilization. To date, various studies into STPV systems have focused on their energy performance based on existing simulation programs, or on the modelling, normally validated by limited experimental data, of the STPV modules thermal behaviour. Taking into account that very limited experimental research has been conducted on the energy performance of STPV elements and that the characterization in real operation conditions is necessary to promote an energetically efficient integration of this technology in the building envelope, an outdoor testing facility has been designed, developed and built at the Solar Energy Institute of the Technical University of Madrid. In this work, the methodology used in the definition of the testing facility, its capability and limitations are presented and discussed.