El papel de los hongos en la conservación de Andosols: estudio de caso en Tlaxcala, México

El estado de Tlaxcala, México, presenta problemas ambientales relacionados con la erosión del suelo; sin embargo, en algunas áreas conformadas por Andosols, bosque de pino y zonas agrícolas, su degradación es mínima. La presencia de micelio abundante en los horizontes subsuperficiales en suelos localizados en pendiente puede ser causa que los suelos se conserven. Los objetivos del estudio fueron caracterizar las propiedades edáficas de suelos en diferente posición geomorfológica, identificar especies de hongos micorrízico arbusculares (HMA) y determinar la relación del micelio con los agregados y las partículas elementales en un Vitric Andosols de Calpulalpan, Tlaxcala, México. Los resultados muestran que los suelos presentaron diferentes secuencias y espesores de cenizas y lapillis pomáceos, de moderada a alta fertilidad. La estructura migajosa dominó en horizontes superiores y granular simple en sub-horizontes. Los horizontes presentaron retención alta de humedad y permeabilidad facilitando el desarrollo micelial y formación de esporas de HMA hasta 120 cm de profundidad. Se registraron 10 especies de HMA y la mas abundante fue Funneliformis mosseae. El análisis micro-morfológico mostró diferentes relaciones entre el micelio, los horizontes y las partículas del suelo, con residuos orgánicos (horizonte O), macro y micro agregados (horizontes A y B), alófano e imogolita (horizonte B) y lapillis (horizonte C). El micelio de los hongos formó redes en todo el suelo y en los lapillis inserta a las partículas de pómez (como cuentas de rosario) a través de los poros vesiculares tubulares lo que le proporciona estabilidad a los Andosols y evita su degradación

A model-independent approach to infer hierarchical codon substitution dynamics

<p>Abstract</p> <p>Background</p> <p>Codon substitution constitutes a fundamental process in molecular biology that has been studied extensively. However, prior studies rely on various assumptions, e.g. regarding the relevance of specific biochemical properties, or on conservation criteria for defining substitution groups. Ideally, one would instead like to analyze the substitution process in terms of raw dynamics, independently of underlying system specifics. In this paper we propose a method for doing this by identifying groups of codons and amino acids such that these groups imply closed dynamics. The approach relies on recently developed spectral and agglomerative techniques for identifying hierarchical organization in dynamical systems.</p> <p>Results</p> <p>We have applied the techniques on an empirically derived Markov model of the codon substitution process that is provided in the literature. Without system specific knowledge of the substitution process, the techniques manage to "blindly" identify multiple levels of dynamics; from amino acid substitutions (via the standard genetic code) to higher order dynamics on the level of amino acid groups. We hypothesize that the acquired groups reflect earlier versions of the genetic code.</p> <p>Conclusions</p> <p>The results demonstrate the applicability of the techniques. Due to their generality, we believe that they can be used to coarse grain and identify hierarchical organization in a broad range of other biological systems and processes, such as protein interaction networks, genetic regulatory networks and food webs.</p

Transverse momentum spectra of charged particles in proton-proton collisions at s=900\sqrt{s} = 900 GeV with ALICE at the LHC

The inclusive charged particle transverse momentum distribution is measured in proton-proton collisions at $\sqrt{s} = 900$ GeV at the LHC using the ALICE detector. The measurement is performed in the central pseudorapidity region $(|\eta|<0.8)$ over the transverse momentum range $0.15<p_{\rm T}<10$ GeV/$c$. The correlation between transverse momentum and particle multiplicity is also studied. Results are presented for inelastic (INEL) and non-single-diffractive (NSD) events. The average transverse momentum for $|\eta|<0.8$ is $\left<p_{\rm T}\right>_{\rm INEL}=0.483\pm0.001$ (stat.) $\pm0.007$ (syst.) GeV/$c$ and \left_{\rm NSD}=0.489\pm0.001 (stat.) $\pm0.007$ (syst.) GeV/$c$, respectively. The data exhibit a slightly larger $\left<p_{\rm T}\right>$ than measurements in wider pseudorapidity intervals. The results are compared to simulations with the Monte Carlo event generators PYTHIA and PHOJET.Comment: 20 pages, 8 figures, 2 tables, published version, figures at http://aliceinfo.cern.ch/ArtSubmission/node/390

Self-organisation of symbolic information

Information is encountered in two different appearances, in native form by arbitrary physical structures, or in symbolic form by coded sequences of letters or the like. The self-organised emergence of symbolic information from structural information is referred to as a ritualisation transition. Occurring at some stage in evolutionary history, ritualisation transitions have in common that after the crossover, arbitrary symbols are issued and recognised by information-processing devices, by transmitters and receivers in the sense of Shannon's communication theory. Symbolic information-processing systems exhibit the fundamental code symmetry whose key features, such as largely lossless copying or persistence under hostile conditions, may elucidate the reasons for the repeated successful occurrence of ritualisation phenomena in evolution history. Ritualisation examples are briefly reviewed such as the origin of life, the appearance of human languages, the establishment of emergent social categories such as money, or the development of digital computers. In addition to their role as carriers of symbolic information, symbols are physical structures which also represent structural information. For a thermodynamic description of symbols and their arrangements, it appears reasonable to distinguish between Boltzmann entropy, Clausius entropy and Pauling entropy. Thermodynamic properties of symbols imply that their lifetimes are limited by the 2nd law

Determining Optimization-Risk Profiles for Individual Decision Makers

Investment funds typically vary with regard to the emphasis that the managers place on acceptable risk and expected returns on investment. This chapter highlight a nonlinear analytic strategy, orbital decomposition (ORBDE) for identifying and extracting patterns of categorical events from time series data. The contributing constructs from symbolic dynamics, chaos, and entropy are described in conjunction with the central ORBDE algorithm. A study in task switching, which can alleviate or induce cognitive fatigue, is used an illustrative example of the basic mode of analysis. The aggregate more of ORBDE allows category codes from multiple variables to be assigned to each event in a time series. An illustrative example of the aggregate mode is presented for risk profile analysis in financial decisions. The results open up many possibilities for studying sequences of decisions made by fund managers and individual investors to determine profiles of risk acceptance, expected returns, and other features of portfolio management

Predicting Secondary Structure for Human Proteins Based on Chou-Fasman Method

Part 2: 8th Mining Humanistic Data WorkshopInternational audienceProteins are constructed by the combination of a different number of amino acids and thus, have a different structure and folding depending on chemical reactions and other aspects. The protein folding prediction can help in many healthcare scenarios to foretell and prevent diseases. The different elements that form a protein give the secondary structure. One of the most common algorithms used for secondary structure prediction constitutes the Chou-Fasman method. This technique divides and in following analyses each amino acid in three different elements, which are -helices, -sheets and turns based on already known protein structures. Its aim is to predict the probability for which each of these elements will be formed. In this paper, we have used Chou-Fasman algorithm for extracting the probabilities of a series of amino acids in FASTA format. We make an analysis given all probabilities for any length of a human protein without any restriction as other existing tools