DPSK signals demodulation based on a multimode fiber with a central dip

Differential Phase Shift Keying (DPSK) modulation format has been shown as a robust solution for next-generation optical transmission systems. One key device enabling such systems is a delay interferometer, converting the phase modulation signal into the intensity modulation signal to be detected by the photodiodes. Usually, a standard Mach-Zehnder interferometer (MZI) is used for demodulating a DPSK signal. In this paper, we develop an MZI which is based on all-fiber Multimode Interference (MI) structure: a multimode fiber (MMF) with a central dip, located between two single-mode fibers (SMFs) without any transition zones. The MI based MZI (MI-MZI) is more stable than the standard MZI as the two arms share the same MMF, reducing the impact of the external effects, such as temperature and others. Performance of this MI-MZI is analyzed theoretically and experimentally from transmission spectrum. Experimental results shows that high interference extinction ratio is obtained, which is far higher than that obtained from a normal graded-index based MI-MZI. Finally, by software simulation, we demonstrate that our proposed MI-MZI can be used for demodulating a 40 Gbps DPSK signal. The performance of the MI-MZI based DPSK receiver is analyzed from the sensitivity. Simulation results show that sensitivity of the proposed receiver is about -22.3 dBm for a BER of 10-15 and about -23.8 dBm for a BER of 10-9.

Signwalling: signals derived from arabiopsis cell wall activate specific resistance to pathogens

The cell wall is a dynamic structure that regulates both constitutive and inducible plant defence responses. Different molecules o DAMPs (damage-associated molecular patterns) can be released from plant cell walls upon pathogen infection or wounding and can trigger immune responses. To further characterize the function of cell wall on the regulation of these immune responses, we have performed a biased resistance screening of putative/well-characterized primary/secondary Arabidopsis thaliana cell wall mutants (cwm). In this screening we have identified more than 20 cwm mutants with altered susceptibility/resistance to at least one of the following pathogens: the necrotrophic fungi Plectosphaerella cucumerina, the vascular bacterium Ralstonia solanacearum, the biotrophic oomycete Hyaloperonospora arabidopsidis and the powdery mildew fungus Erisyphe cruciferarum. We found that cell wall extracts from some of these cwm plants contain novel DAMPs that activate immune responses and conferred enhanced resistance to particular pathogens when they were applied to wild-type plants. Using glycomic profiling we have performed an initial characterization of the active carbohydrate structures present in these cwm wall fractions, and we have determined the signalling pathways regulated by thesse fractions. . The data generated with this collection of wall mutants support the existence of specific correlations between cell wall structure/composition, resistance to particular type of pathogens and plant fitness. Remarkably, we have identified specific cwm mutations that uncoupled resistance to pathogens from plant trade-offs, further indicating the plasticity of wall structures in the regulation of plant immune responses.

Modelo de gestión de un embalse en tiempo real durante avenidas basado en redes bayesianas entrenadas con el método de optimización PLEM

En la actualidad, la gestión de embalses para el control de avenidas se realiza, comúnmente, utilizando modelos de simulación. Esto se debe, principalmente, a su facilidad de uso en tiempo real por parte del operador de la presa. Se han desarrollado modelos de optimización de la gestión del embalse que, aunque mejoran los resultados de los modelos de simulación, su aplicación en tiempo real se hace muy difícil o simplemente inviable, pues está limitada al conocimiento de la avenida futura que entra al embalse antes de tomar la decisión de vertido. Por esta razón, se ha planteado el objetivo de desarrollar un modelo de gestión de embalses en avenidas que incorpore las ventajas de un modelo de optimización y que sea de fácil uso en tiempo real por parte del gestor de la presa. Para ello, se construyó un modelo de red Bayesiana que representa los procesos de la cuenca vertiente y del embalse y, que aprende de casos generados sintéticamente mediante un modelo hidrológico agregado y un modelo de optimización de la gestión del embalse. En una primera etapa, se generó un gran número de episodios sintéticos de avenida utilizando el método de Monte Carlo, para obtener las lluvias, y un modelo agregado compuesto de transformación lluvia- escorrentía, para obtener los hidrogramas de avenida. Posteriormente, se utilizaron las series obtenidas como señales de entrada al modelo de gestión de embalses PLEM, que optimiza una función objetivo de costes mediante programación lineal entera mixta, generando igual número de eventos óptimos de caudal vertido y de evolución de niveles en el embalse. Los episodios simulados fueron usados para entrenar y evaluar dos modelos de red Bayesiana, uno que pronostica el caudal de entrada al embalse, y otro que predice el caudal vertido, ambos en un horizonte de tiempo que va desde una a cinco horas, en intervalos de una hora. En el caso de la red Bayesiana hidrológica, el caudal de entrada que se elige es el promedio de la distribución de probabilidad de pronóstico. En el caso de la red Bayesiana hidráulica, debido al comportamiento marcadamente no lineal de este proceso y a que la red Bayesiana devuelve un rango de posibles valores de caudal vertido, se ha desarrollado una metodología para seleccionar un único valor, que facilite el trabajo del operador de la presa. Esta metodología consiste en probar diversas estrategias propuestas, que incluyen zonificaciones y alternativas de selección de un único valor de caudal vertido en cada zonificación, a un conjunto suficiente de episodios sintéticos. Los resultados de cada estrategia se compararon con el método MEV, seleccionándose las estrategias que mejoran los resultados del MEV, en cuanto al caudal máximo vertido y el nivel máximo alcanzado por el embalse, cualquiera de las cuales puede usarse por el operador de la presa en tiempo real para el embalse de estudio (Talave). La metodología propuesta podría aplicarse a cualquier embalse aislado y, de esta manera, obtener, para ese embalse particular, diversas estrategias que mejoran los resultados del MEV. Finalmente, a modo de ejemplo, se ha aplicado la metodología a una avenida sintética, obteniendo el caudal vertido y el nivel del embalse en cada intervalo de tiempo, y se ha aplicado el modelo MIGEL para obtener en cada instante la configuración de apertura de los órganos de desagüe que evacuarán el caudal. Currently, the dam operator for the management of dams uses simulation models during flood events, mainly due to its ease of use in real time. Some models have been developed to optimize the management of the reservoir to improve the results of simulation models. However, real-time application becomes very difficult or simply unworkable, because the decision to discharge depends on the unknown future avenue entering the reservoir. For this reason, the main goal is to develop a model of reservoir management at avenues that incorporates the advantages of an optimization model. At the same time, it should be easy to use in real-time by the dam manager. For this purpose, a Bayesian network model has been developed to represent the processes of the watershed and reservoir. This model learns from cases generated synthetically by a hydrological model and an optimization model for managing the reservoir. In a first stage, a large number of synthetic flood events was generated using the Monte Carlo method, for rain, and rain-added processing model composed of runoff for the flood hydrographs. Subsequently, the series obtained were used as input signals to the reservoir management model PLEM that optimizes a target cost function using mixed integer linear programming. As a result, many optimal discharge rate events and water levels in the reservoir levels were generated. The simulated events were used to train and test two models of Bayesian network. The first one predicts the flow into the reservoir, and the second predicts the discharge flow. They work in a time horizon ranging from one to five hours, in intervals of an hour. In the case of hydrological Bayesian network, the chosen inflow is the average of the probability distribution forecast. In the case of hydraulic Bayesian network the highly non-linear behavior of this process results on a range of possible values of discharge flow. A methodology to select a single value has been developed to facilitate the dam operator work. This methodology tests various strategies proposed. They include zoning and alternative selection of a single value in each discharge rate zoning from a sufficient set of synthetic episodes. The results of each strategy are compared with the MEV method. The strategies that improve the outcomes of MEV are selected and can be used by the dam operator in real time applied to the reservoir study case (Talave). The methodology could be applied to any single reservoir and, thus, obtain, for the particular reservoir, various strategies that improve results from MEV. Finally, the methodology has been applied to a synthetic flood, obtaining the discharge flow and the reservoir level in each time interval. The open configuration floodgates to evacuate the flow at each interval have been obtained applying the MIGEL model.

Human activity recognition by inertial signals obtained from a smartphone

Human Activity Recognition (HAR) is an emerging research field with the aim to identify the actions carried out by a person given a set of observations and the surrounding environment. The wide growth in this research field inside the scientific community is mainly explained by the high number of applications that are arising in the last years. A great part of the most promising applications are related to the healthcare field, where it is possible to track the mobility of patients with motor dysfunction as also the physical activity in patients with cardiovascular risk. Until a few years ago, by using distinct kind of sensors, a patient follow-up was possible. However, far from being a long-term solution and with the smartphone irruption, that monitoring can be achieved in a non-invasive way by using the embedded smartphone’s sensors. For these reasons this Final Degree Project arises with the main target to evaluate new feature extraction techniques in order to carry out an activity and user recognition, and also an activity segmentation. The recognition is done thanks to the inertial signals integration obtained by two widespread sensors in the greater part of smartphones: accelerometer and gyroscope. In particular, six different activities are evaluated walking, walking-upstairs, walking-downstairs, sitting, standing and lying. Furthermore, a segmentation task is carried out taking into account the activities performed by thirty users. This can be done by using Hidden Markov Models and also a set of tools tested satisfactory in speech recognition: HTK (Hidden Markov Model Toolkit).

Waves, analytical signals, and some postulates of quantum theory

In this paper we apply the formalism of the analytical signal theory to the Schrödinger wavefunction. Making use exclusively of the wave-particle duality and the rinciple of relativistic covariance, we actually derive the form of the quantum energy and momentum operators for a single nonrelativistic particle. Without using any more quantum postulates, and employing the formalism of the characteristic function, we also derive the quantum-mechanical prescription for the measurement probability in such cases.

Human activity recognition by inertial signals obtained from a smartphone

El Reconocimiento de Actividades Humanas es un área de investigación emergente, cuyo objetivo principal es identificar las acciones realizadas por un sujeto analizando las señales obtenidas a partir de unos sensores. El rápido crecimiento de este área de investigación dentro de la comunidad científica se explica, en parte, por el elevado número de aplicaciones que están surgiendo en los últimos años. Gran parte de las aplicaciones más prometedoras se encuentran en el campo de la salud, donde se puede hacer un seguimiento del nivel de movilidad de pacientes con trastornos motores, así como monitorizar el nivel de actividad física en pacientes con riesgo cardiovascular. Hasta hace unos años, mediante el uso de distintos tipos de sensores se podía hacer un seguimiento del paciente. Sin embargo, lejos de ser una solución a largo plazo y gracias a la irrupción del teléfono inteligente, este seguimiento se puede hacer de una manera menos invasiva, haciendo uso de la gran variedad de sensores integrados en este tipo de dispositivos. En este contexto nace este Trabajo de Fin de Grado, cuyo principal objetivo es evaluar nuevas técnicas de extracción de características para llevar a cabo un reconocimiento de actividades y usuarios así como una segmentación de aquellas. Este reconocimiento se hace posible mediante la integración de señales inerciales obtenidas por dos sensores presentes en la gran mayoría de teléfonos inteligentes: acelerómetro y giróscopo. Concretamente, se evalúan seis tipos de actividades realizadas por treinta usuarios: andar, subir escaleras, bajar escaleras, estar sentado, estar de pie y estar tumbado. Además y de forma paralela, se realiza una segmentación temporal de los distintos tipos de actividades realizadas por dichos usuarios. Todo ello se llevará a cabo haciendo uso de los Modelos Ocultos de Markov, así como de un conjunto de herramientas probadas satisfactoriamente en reconocimiento del habla: HTK (Hidden Markov Model Toolkit).

A perceptual memory for low-contrast visual signals

Detection of a visual signal can be facilitated by simultaneous presentation of a similar subthreshold signal. Here we show that the facilitatory effect of a subthreshold signal can persist for more than 16 s. Presenting a near-threshold Gabor signal (prime) produced a phase-independent increase in contrast sensitivity (40%) to similar successive signals (target) for a period of up to 16 s. This effect was obtained only when both prime and target were presented to the same eye. We further show that the memory trace is inactivated by presenting high-contrast signals before the target. These results suggest that activated neurons in the primary visual cortex retain a near-threshold memory trace that persists until reactivated.

Ultrafast signals in protein folding and the polypeptide contracted state

To test the significance of ultrafast protein folding signals (≪1 msec), we studied cytochrome c (Cyt c) and two Cyt c fragments with major C-terminal segments deleted. The fragments remain unfolded under all conditions and so could be used to define the unfolded baselines for protein fluorescence and circular dichroism (CD) as a function of denaturant concentration. When diluted from high to low denaturant in kinetic folding experiments, the fragments readjust to their new baseline values in a “burst phase” within the mixing dead time. The fragment burst phase reflects a contraction of the polypeptide from a more extended unfolded condition at high denaturant to a more contracted unfolded condition in the poorer, low denaturant solvent. Holo Cyt c exhibits fluorescence and CD burst phase signals that are essentially identical to the fragment signals over the whole range of final denaturant concentrations, evidently reflecting the same solvent-dependent, relatively nonspecific contraction and not the formation of a specific folding intermediate. The significance of fast folding signals in Cyt c and other proteins is discussed in relation to the hypothesis of an initial rate-limiting search-nucleation-collapse step in protein folding [Sosnick, T. R., Mayne, L. & Englander, S. W. (1996) Proteins Struct. Funct. Genet. 24, 413–426].

Reciprocal secretion of proteins by the bacterial type III machines of plant and animal pathogens suggests universal recognition of mRNA targeting signals

Bacterial pathogens of both animals and plants use type III secretion machines to inject virulence proteins into host cells. Although many components of the secretion machinery are conserved among different bacterial species, the substrates for their type III pathways are not. The Yersinia type III machinery recognizes some secretion substrates via a signal that is encoded within the first 15 codons of yop mRNA. These signals can be altered by frameshift mutations without affecting secretion of the encoded polypeptides, suggesting a mechanism whereby translation of yop mRNA is coupled to the translocation of newly synthesized polypeptide. We report that the type III machinery of Erwinia chrysanthemi cloned in Escherichia coli recognizes the secretion signals of yopE and yopQ. Pseudomonas syringae AvrB and AvrPto, two proteins exported by the recombinant Erwinia machine, can also be secreted by the Yersinia type III pathway. Mapping AvrPto sequences sufficient for the secretion of reporter fusions in Yersinia revealed the presence of an mRNA secretion signal. We propose that 11 conserved components of type III secretion machines may recognize signals that couple mRNA translation to polypeptide secretion.

Pattern of neuronal activity associated with conscious and unconscious processing of visual signals

Following striate cortex damage in monkeys and humans there can be residual function mediated by parallel visual pathways. In humans this can sometimes be associated with a “feeling” that something has happened, especially with rapid movement or abrupt onset. For less transient events, discriminative performance may still be well above chance even when the subject reports no conscious awareness of the stimulus. In a previous study we examined parameters that yield good residual visual performance in the “blind” hemifield of a subject with unilateral damage to the primary visual cortex. With appropriate parameters we demonstrated good discriminative performance, both with and without conscious awareness of a visual event. These observations raise the possibility of imaging the brain activity generated in the “aware” and the “unaware” modes, with matched levels of discrimination performance, and hence of revealing patterns of brain activation associated with visual awareness. The intact hemifield also allows a comparison with normal vision. Here we report the results of a functional magnetic resonance imaging study on the same subject carried out under aware and unaware stimulus conditions. The results point to a shift in the pattern of activity from neocortex in the aware mode, to subcortical structures in the unaware mode. In the aware mode prestriate and dorsolateral prefrontal cortices (area 46) are active. In the unaware mode the superior colliculus is active, together with medial and orbital prefrontal cortical sites.

Yersinia signals macrophages to undergo apoptosis and YopJ is necessary for this cell death

Pathogenic Yersinia spp. carry a large common plasmid that encodes a number of essential virulence determinants. Included in these factors are the Yersinia-secreted proteins called Yops. We analyzed the consequences of wild-type and mutant strains of Yersinia pseudotuberculosis interactions with the macrophage cell line RAW264.7 and murine bone marrow-derived macrophages. Wild-type Y. pseudotuberculosis kills ≈70% of infected RAW264.7 macrophages and marrow-derived macrophages after an 8-h infection. We show that the cell death mediated by Y. pseudotuberculosis is apoptosis. Mutant Y. pseudotuberculosis that do not make any Yop proteins no longer cause host cell death. Attachment to host cells via invasin or YadA is necessary for the cell death phenotype. Several Yop mutant strains that fail to express one or more Yop proteins were engineered and then characterized for their ability to cause host cell death. A mutant with a polar insertion in YpkA Ser/Thr kinase that does not express YpkA or YopJ is no longer able to cause apoptosis. In contrast, a mutant no longer making YopE or YopH (a tyrosine phosphatase) induces apoptosis in macrophages similar to wild type. When yopJ is added in trans to the ypkAyopJ mutant, the ability of this strain to signal programmed cell death in macrophages is restored. Thus, YopJ is necessary for inducing apoptosis. The ability of Y. pseudotuberculosis to promote apoptosis of macrophages in cell culture suggests that this process is important for the establishment of infection in the host and for evasion of the host immune response.

The Aer protein and the serine chemoreceptor Tsr independently sense intracellular energy levels and transduce oxygen, redox, and energy signals for Escherichia coli behavior

We identified a protein, Aer, as a signal transducer that senses intracellular energy levels rather than the external environment and that transduces signals for aerotaxis (taxis to oxygen) and other energy-dependent behavioral responses in Escherichia coli. Domains in Aer are similar to the signaling domain in chemotaxis receptors and the putative oxygen-sensing domain of some transcriptional activators. A putative FAD-binding site in the N-terminal domain of Aer shares a consensus sequence with the NifL, Bat, and Wc-1 signal-transducing proteins that regulate gene expression in response to redox changes, oxygen, and blue light, respectively. A double mutant deficient in aer and tsr, which codes for the serine chemoreceptor, was negative for aerotaxis, redox taxis, and glycerol taxis, each of which requires the proton motive force and/or electron transport system for signaling. We propose that Aer and Tsr sense the proton motive force or cellular redox state and thereby integrate diverse signals that guide E. coli to environments where maximal energy is available for growth.

From calcium blips to calcium puffs: Theoretical analysis of the requirements for interchannel communication

In the cytoplasm of cells of different types, discrete clusters of inositol 1,4,5-trisphosphate-sensitive Ca2+ channels generate Ca2+ signals of graded size, ranging from blips, which involve the opening of only one channel, to moderately larger puffs, which result from the concerted opening of a few channels in the same cluster. These channel clusters are of unknown size or geometrical characteristics. The aim of this study was to estimate the number of channels and the interchannel distance within such a cluster. Because these characteristics are not attainable experimentally, we performed computer stochastic simulations of Ca2+ release events. We conclude that, to ensure efficient interchannel communication, as experimentally observed, a typical cluster should contain two or three tens of inositol 1,4,5-trisphosphate-sensitive Ca2+ channels in close contact.

In silico detection of control signals: mRNA 3′-end-processing sequences in diverse species

We have investigated mRNA 3′-end-processing signals in each of six eukaryotic species (yeast, rice, arabidopsis, fruitfly, mouse, and human) through the analysis of more than 20,000 3′-expressed sequence tags. The use and conservation of the canonical AAUAAA element vary widely among the six species and are especially weak in plants and yeast. Even in the animal species, the AAUAAA signal does not appear to be as universal as indicated by previous studies. The abundance of single-base variants of AAUAAA correlates with their measured processing efficiencies. As found previously, the plant polyadenylation signals are more similar to those of yeast than to those of animals, with both common content and arrangement of the signal elements. In all species examined, the complete polyadenylation signal appears to consist of an aggregate of multiple elements. In light of these and previous results, we present a broadened concept of 3′-end-processing signals in which no single exact sequence element is universally required for processing. Rather, the total efficiency is a function of all elements and, importantly, an inefficient word in one element can be compensated for by strong words in other elements. These complex patterns indicate that effective tools to identify 3′-end-processing signals will require more than consensus sequence identification.

An alternative pathway for rod signals in the rodent retina: Rod photoreceptors, cone bipolar cells, and the localization of glutamate receptors

In the mammalian retina, extensive processing of spatiotemporal and chromatic information occurs. One key principle in signal transfer through the retina is parallel processing. Two of these parallel pathways are the ON- and OFF-channels transmitting light and dark signals. This dual system is created in the outer plexiform layer, the first relay station in retinal signal transfer. Photoreceptors release glutamate onto ON- and OFF-type bipolar cells, which are functionally distinguished by their postsynaptic expression of different types of glutamate receptors, namely ionotropic and metabotropic glutamate receptors. In the current concept, rod photoreceptors connect only to rod bipolar cells (ON-type) and cone photoreceptors connect only to cone bipolar cells (ON- and OFF-type). We have studied the distribution of (RS)-α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) glutamate receptor subunits at the synapses in the outer plexiform layer of the rodent retina by immunoelectron microscopy and serial section reconstruction. We report a non-classical synaptic contact and an alternative pathway for rod signals in the retina. Rod photoreceptors made synaptic contact with putative OFF-cone bipolar cells that expressed the AMPA glutamate receptor subunits GluR1 and GluR2 on their dendrites. Thus, in the retina of mouse and rat, an alternative pathway for rod signals exists, where rod photoreceptors bypass the rod bipolar cell and directly excite OFF-cone bipolar cells through an ionotropic sign-conserving AMPA glutamate receptor.