Chemosensory response of marine flagellate towards L- and D- dissolved free amino acids generated during heavy grazing on bacteria

This study investigated the generation of dissolved free amino acids (DFAA) by the bacterivorous flagellate Rhynchomonas nasuta when feeding on abundant prey. Specifically, it examined whether this flagellate protist exhibits a chemosensory response towards those amino acids. The concentrations of glycine and the and D-enantiomers of glutamate, serine, threonine, alanine, and leucine were determined in co-cultures of the flagellate and bacteria. Glycine, L- and D-alanine, and L-serine were found to accumulate under these conditions in amounts that correlated positively with flagellate abundance, suggesting that protists are involved in their generation. Investigations of the chemotactic response of young and old foraging protists to the same amino acids, offered in concentrations similar to those previously generated, showed that glycine elicited the strongest attraction in both age groups. Young protists were strongly attracted to all the assayed amino acids, whereas older protists maintained a high level of attraction only for glycine. These results suggest that glycine generated by protists actively grazing in bacterially enriched patches functions as an infochemical, signaling to foraging protists the presence of available prey in the aquatic environment.

Lo visual como construcción. Desarrollo de un modelo pictórico de representación de la imagen

903 páginas, bibliografía en páginas 854-895, glosario en páginas 896-903

New methods for generating populations in Markov network based EDAs: Decimation strategies and model-based template recombination

Methods for generating a new population are a fundamental component of estimation of distribution algorithms (EDAs). They serve to transfer the information contained in the probabilistic model to the new generated population. In EDAs based on Markov networks, methods for generating new populations usually discard information contained in the model to gain in efficiency. Other methods like Gibbs sampling use information about all interactions in the model but are computationally very costly. In this paper we propose new methods for generating new solutions in EDAs based on Markov networks. We introduce approaches based on inference methods for computing the most probable configurations and model-based template recombination. We show that the application of different variants of inference methods can increase the EDAs’ convergence rate and reduce the number of function evaluations needed to find the optimum of binary and non-binary discrete functions.

USP1 deubiquitinase: cellular functions, regulatory mechanisms and emerging potential as target in cancer therapy

12 p.

RCeveierwamide and ceramide 1-phosphate in health and disease

Sphingolipids are essential components of cell membranes, and many of them regulate vital cell functions. In particular, ceramide plays crucial roles in cell signaling processes. Two major actions of ceramides are the promotion of cell cycle arrest and the induction of apoptosis. Phosphorylation of ceramide produces ceramide 1-phosphate (C1P), which has opposite effects to ceramide. C1P is mitogenic and has prosurvival properties. In addition, C1P is an important mediator of inflammatory responses, an action that takes place through stimulation of cytosolic phospholipase A2, and the subsequent release of arachidonic acid and prostaglandin formation. All of the former actions are thought to be mediated by intracellularly generated C1P. However, the recent observation that C1P stimulates macrophage chemotaxis implicates specific plasma membrane receptors that are coupled to Gi proteins. Hence, it can be concluded that C1P has dual actions in cells, as it can act as an intracellular second messenger to promote cell survival, or as an extracellular receptor agonist to stimulate cell migration.

Literature Review of Integrated Impact Assessment Models of Climate Change with Emphasis on Damage Functions

35 p.

Properties of convergence of a class of iterative processes generated by sequences of self-mappings with applications to switched dynamic systems

This article investigates the convergence properties of iterative processes involving sequences of self-mappings of metric or Banach spaces. Such sequences are built from a set of primary self-mappings which are either expansive or non-expansive self-mappings and some of the non-expansive ones can be contractive including the case of strict contractions. The sequences are built subject to switching laws which select each active self-mapping on a certain activation interval in such a way that essential properties of boundedness and convergence of distances and iterated sequences are guaranteed. Applications to the important problem of stability of dynamic switched systems are also given.

Frame presentations: variants of the reals, rings of functions, their Dedekind completions, and the unit circle

176 p.

Quantum Simulation of Dissipative Processes without Reservoir Engineering

We present a quantum algorithm to simulate general finite dimensional Lindblad master equations without the requirement of engineering the system-environment interactions. The proposed method is able to simulate both Markovian and non-Markovian quantum dynamics. It consists in the quantum computation of the dissipative corrections to the unitary evolution of the system of interest, via the reconstruction of the response functions associated with the Lindblad operators. Our approach is equally applicable to dynamics generated by effectively non-Hermitian Hamiltonians. We confirm the quality of our method providing specific error bounds that quantify its accuracy.

Energy demands of diverse spiking cells from the neocortex, hippocampus, and thalamus

It has long been known that neurons in the brain are not physiologically homogeneous. In response to current stimulus, they can fire several distinct patterns of action potentials that are associated with different physiological classes ranging from regular-spiking cells, fast-spiking cells, intrinsically bursting cells, and low-threshold cells. In this work we show that the high degree of variability in firing characteristics of action potentials among these cells is accompanied with a significant variability in the energy demands required to restore the concentration gradients after an action potential. The values of the metabolic energy were calculated for a wide range of cell temperatures and stimulus intensities following two different approaches. The first one is based on the amount of Na+ load crossing the membrane during a single action potential, while the second one focuses on the electrochemical energy functions deduced from the dynamics of the computational neuron models. The results show that the thalamocortical relay neuron is the most energy-efficient cell consuming between 7 and 18 nJ/cm(2) for each spike generated, while both the regular and fast spiking cells from somatosensory cortex and the intrinsically-bursting cell from a cat visual cortex are the least energy-efficient, and can consume up to 100 nJ/cm(2) per spike. The lowest values of these energy demands were achieved at higher temperatures and high external stimuli.

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

206 p.

Bessel functions and equations of mathematical physics

The aim of this dissertation is to introduce Bessel functions to the reader, as well as studying some of their properties. Moreover, the final goal of this document is to present the most well- known applications of Bessel functions in physics.

Can environmental constraints determine random patterns of plant species co-occurrence?

Plant community ecologists use the null model approach to infer assembly processes from observed patterns of species co-occurrence. In about a third of published studies, the null hypothesis of random assembly cannot be rejected. When this occurs, plant ecologists interpret that the observed random pattern is not environmentally constrained - but probably generated by stochastic processes. The null model approach (using the C-score and the discrepancy index) was used to test for random assembly under two simulation algorithms. Logistic regression, distance-based redundancy analysis, and constrained ordination were used to test for environmental determinism (species segregation along environmental gradients or turnover and species aggregation). This article introduces an environmentally determined community of alpine hydrophytes that presents itself as randomly assembled. The pathway through which the random pattern arises in this community is suggested to be as follows: Two simultaneous environmental processes, one leading to species aggregation and the other leading to species segregation, concurrently generate the observed pattern, which results to be neither aggregated nor segregated - but random. A simulation study supports this suggestion. Although apparently simple, the null model approach seems to assume that a single ecological factor prevails or that if several factors decisively influence the community, then they all exert their influence in the same direction, generating either aggregation or segregation. As these assumptions are unlikely to hold in most cases and assembly processes cannot be inferred from random patterns, we would like to propose plant ecologists to investigate specifically the ecological processes responsible for observed random patterns, instead of trying to infer processes from patterns