Competing regression models for longitudinal data

The choice of an appropriate family of linear models for the analysis of longitudinal data is often a matter of concern for practitioners. To attenuate such difficulties, we discuss some issues that emerge when analyzing this type of data via a practical example involving pretestposttest longitudinal data. In particular, we consider log-normal linear mixed models (LNLMM), generalized linear mixed models (GLMM), and models based on generalized estimating equations (GEE). We show how some special features of the data, like a nonconstant coefficient of variation, may be handled in the three approaches and evaluate their performance with respect to the magnitude of standard errors of interpretable and comparable parameters. We also show how different diagnostic tools may be employed to identify outliers and comment on available software. We conclude by noting that the results are similar, but that GEE-based models may be preferable when the goal is to compare the marginal expected responses.

Determination of the critical coupling of explosive synchronization transitions in scale-free networks by mean-field approximations

An explosive synchronization can be observed in scale-free networks when Kuramoto oscillators have natural frequencies equal to their number of connections. The present paper reports on mean-field approximations to determine the critical coupling of such explosive synchronization. It has been verified that the equation obtained for the critical coupling has an inverse dependence on the network average degree. This expression differs from those whose frequency distributions are unimodal and even. In this case, the critical coupling depends on the ratio between the first and second statistical moments of the degree distribution. Numerical simulations were also conducted to verify our analytical results.

Database of diazotrophs in global ocean: abundances, biomass and nitrogen fixation rates

[EN] Marine N2 fixing microorganisms, termed diazotrophs, are a key functional group in marine pelagic ecosystems. The biological fixation of dinitrogen (N2) to bioavailable nitrogen provides an important new source of nitrogen for pelagic marine ecosystems 5 and influences primary productivity and organic matter export to the deep ocean. As one of a series of efforts to collect biomass and rates specific to different phytoplankton functional groups, we have constructed a database on diazotrophic organisms in the global pelagic upper ocean by compiling about 12 000 direct field measurements of cyanobacterial diazotroph abundances (based on microscopic cell counts or qPCR 10 assays targeting the nifH genes) and N2 fixation rates. Biomass conversion factors are estimated based on cell sizes to convert  abundance data to diazotrophic biomass. The database is limited spatially, lacking large regions of the ocean especially in the Indian Ocean. The data are approximately log-normal distributed, and large variances exist in most sub-databases with non-zero values differing 5 to 8 orders of magnitude. 15 Lower mean N2 fixation rate was found in the North Atlantic Ocean than the Pacific Ocean. Reporting the geometric mean and the range of one geometric standard error below and above the geometric mean, the pelagic N2 fixation rate in the global ocean is estimated to be 62 (53–73) TgNyr−1 and the pelagic diazotrophic biomass in the global ocean is estimated to be 4.7 (2.3–9.6) TgC from cell counts and to 89 (40–20 200) TgC from nifH-based abundances. Uncertainties related to biomass conversion factors can change the estimate of geometric mean pelagic diazotrophic biomass in the global ocean by about ±70 %. This evolving database can be used to study spatial and temporal distributions and variations of marine N2 fixation, to validate geochemical estimates and to parameterize and validate biogeochemical models. The database is 25 stored in PANGAEA (http://doi.pangaea.de/10.1594/PANGAEA.774851).

Fading pdf of free-space optical communication system with pointing error

A free-space optical (FSO) laser communication system with perfect fast-tracking experiences random power fading due to atmospheric turbulence. For a FSO communication system without fast-tracking or with imperfect fast-tracking, the fading probability density function (pdf) is also affected by the pointing error. In this thesis, the overall fading pdfs of FSO communication system with pointing errors are calculated using an analytical method based on the fast-tracked on-axis and off-axis fading pdfs and the fast-tracked beam profile of a turbulence channel. The overall fading pdf is firstly studied for the FSO communication system with collimated laser beam. Large-scale numerical wave-optics simulations are performed to verify the analytically calculated fading pdf with collimated beam under various turbulence channels and pointing errors. The calculated overall fading pdfs are almost identical to the directly simulated fading pdfs. The calculated overall fading pdfs are also compared with the gamma-gamma (GG) and the log-normal (LN) fading pdf models. They fit better than both the GG and LN fading pdf models under different receiver aperture sizes in all the studied cases. Further, the analytical method is expanded to the FSO communication system with beam diverging angle case. It is shown that the gamma pdf model is still valid for the fast-tracked on-axis and off-axis fading pdfs with point-like receiver aperture when the laser beam is propagated with beam diverging angle. Large-scale numerical wave-optics simulations prove that the analytically calculated fading pdfs perfectly fit the overall fading pdfs for both focused and diverged beam cases. The influence of the fast-tracked on-axis and off-axis fading pdfs, the fast-tracked beam profile, and the pointing error on the overall fading pdf is also discussed. At last, the analytical method is compared with the previous heuristic fading pdf models proposed since 1970s. Although some of previously proposed fading pdf models provide close fit to the experiment and simulation data, these close fits only exist under particular conditions. Only analytical method shows accurate fit to the directly simulated fading pdfs under different turbulence strength, propagation distances, receiver aperture sizes and pointing errors.

Membrane trafficking from lysosomes to the plasma membrane regulates phosphatidylserine externalization during apoptosis

Programmed cell death is characterized by tightly controlled temporal and spatial intracellular Ca2+ responses that regulate the release of key proapoptotic proteins from mitochondria to the cytosol. Since apoptotic cells retain their ability to exclude membrane impermeable dyes, it is possible that the cells evoke repair mechanisms that, similar to those in normal cells, patch any damaged areas of the plasma membrane that preclude dye permeation. One critical distinction between plasma membrane repair in normal and apoptotic cells is the preservation of membrane lipid asymmetry. In normal cells, phosphatidylserine (PS) retains its normal asymmetric distribution in the inner membrane leaflet. In apoptotic cells, PS redistributes to the outer membrane leaflet by a Ca2+ dependent mechanism where it serves as a recognition ligand for phagocytes(1). In this study Ca 2+-specific fluorescent probes were employed to investigate the source of Ca2+ required for PS externalization. Experiments employing Rhod2-AM, calcium green 1, fura2-AM and the aqueous space marker FITC-dextran, demonstrated that exogenous Ca2+ imported with endocytotic vesicles into the cell was released into the cytosol in an apoptosis dependent manner. Labeling of the luminal side of the endocytotic vesicles with FITC-annexin 5, revealed that membrane lipid asymmetry was disrupted upon endosome formation. Specific labeling of the lysosomal luminal surface with the non-exchangeable membrane lipid probe, N-rhodamine-labeled-phosphatidylethanolamine (N-Rho-PE) and the lysosomal specific probe, lysotracker green, facilitated real-time monitoring of plasma membrane-to-endosome-to-lysosome transitions. Enforced elevation of cytosolic [Ca2+] with ionophore resulted in the redistribution of N-Rho-PE and PS from the inner membrane leaflet to the PM outer membrane leaflet. Identical results were obtained during apoptosis, however, the redistribution of both N-RhoPE and PS was dependent on the release of intra-lysosomal Ca2+ to the cytosol. Additional experiments suggested that lipid redistribution was dependent on the activity of lysosomal phospholipase A2 activity since lipid trafficking was abolished in the presence of chloroquine and lipase inhibitors. These data indicate that endosomal/lysosomal Ca2+ and the fusion of hybrid organelles to the plasma membrane regulates the externalization of PS during apoptosis. ^

THE CHLOREX TREATABILITY STUDY: ENVIRONMENTAL FATE IN FACULTATIVE ANAEROBIC AND AEROBIC WASTE STABILIZATION PONDS (BIODEGRADATION, VOLATILIZATION, SORPTION, PRIORITY POLLUTANTS)

The efficacy of waste stabilization lagoons for the treatment of five priority pollutants and two widely used commercial compounds was evaluated in laboratory model ponds. Three ponds were designed to simulate a primary anaerobic lagoon, a secondary facultative lagoon, and a tertiary aerobic lagoon. Biodegradation, volatilization, and sorption losses were quantified for bis(2-chloroethyl) ether, benzene, toluene, naphthalene, phenanthrene, ethylene glycol, and ethylene glycol monoethyl ether. A statistical model using a log normal transformation indicated biodegradation of bis(2-chloroethyl) ether followed first-order kinetics. Additionally, multiple regression analysis indicated biochemical oxygen demand was the water quality variable most highly correlated with bis(2-chloroethyl) ether effluent concentration. ^

Community Structure in Soil Porous System

Diffusion controls the gaseous transport process in soils when advective transport is almost null. Knowledge of the soil structure and pore connectivity are critical issues to understand and modelling soil aeration, sequestration or emission of greenhouse gasses, volatilization of volatile organic chemicals among other phenomena. In the last decades these issues increased our attention as scientist have realize that soil is one of the most complex materials on the earth, within which many biological, physical and chemical processes that support life and affect climate change take place. A quantitative and explicit characterization of soil structure is difficult because of the complexity of the pore space. This is the main reason why most theoretical approaches to soil porosity are idealizations to simplify this system. In this work, we proposed a more realistic attempt to capture the complexity of the system developing a model that considers the size and location of pores in order to relate them into a network. In the model we interpret porous soils as heterogeneous networks where pores are represented by nodes, characterized by their size and spatial location, and the links representing flows between them. In this work we perform an analysis of the community structure of porous media of soils represented as networks. For different real soils samples, modelled as heterogeneous complex networks, spatial communities of pores have been detected depending on the values of the parameters of the porous soil model used. These types of models are named as Heterogeneous Preferential Attachment (HPA). Developing an exhaustive analysis of the model, analytical solutions are obtained for the degree densities and degree distribution of the pore networks generated by the model in the thermodynamic limit and shown that the networks exhibit similar properties to those observed in other complex networks. With the aim to study in more detail topological properties of these networks, the presence of soil pore community structures is studied. The detection of communities of pores, as groups densely connected with only sparser connections between groups, could contribute to understand the mechanisms of the diffusion phenomena in soils.

Community Structurein Soil Porous System.

Soil is well recognized as a highly complex system. The interaction and coupled physical, chemical, and biological processes and phenomena occurring in the soil environment at different spatial and temporal scales are the main reasons for such complexity. There is a need for appropriate methodologies to characterize soil porous systems with an interdisciplinary character. Four different real soil samples, presenting different textures, have been modeled as heterogeneous complex networks, applying a model known as the heterogeneous preferential attachment. An analytical study of the degree distributions in the soil model shows a multiscaling behavior in the connectivity degrees, leaving an empirically testable signature of heterogeneity in the topology of soil pore networks. We also show that the power-law scaling in the degree distribution is a robust trait of the soil model. Last, the detection of spatial pore communities, as densely connected groups with only sparser connections between them, has been studied for the first time in these soil networks. Our results show that the presence of these communities depends on the parameter values used to construct the network. These findings could contribute to understanding the mechanisms of the diffusion phenomena in soils, such as gas and water diffusion, development and dynamics of microorganisms, among others.

Time series irreversibility: a visibility graph approach

We propose a method to measure real-valued time series irreversibility which combines two different tools: the horizontal visibility algorithm and the Kullback-Leibler divergence. This method maps a time series to a directed network according to a geometric criterion. The degree of irreversibility of the series is then estimated by the Kullback-Leibler divergence (i.e. the distinguishability) between the in and out degree distributions of the associated graph. The method is computationally efficient and does not require any ad hoc symbolization process. We find that the method correctly distinguishes between reversible and irreversible stationary time series, including analytical and numerical studies of its performance for: (i) reversible stochastic processes (uncorrelated and Gaussian linearly correlated), (ii) irreversible stochastic processes (a discrete flashing ratchet in an asymmetric potential), (iii) reversible (conservative) and irreversible (dissipative) chaotic maps, and (iv) dissipative chaotic maps in the presence of noise. Two alternative graph functionals, the degree and the degree-degree distributions, can be used as the Kullback-Leibler divergence argument. The former is simpler and more intuitive and can be used as a benchmark, but in the case of an irreversible process with null net current, the degree-degree distribution has to be considered to identify the irreversible nature of the series

Modeling the evolution of item rating networks using time-domain preferential attachment

The understanding of the structure and dynamics of the intricate network of connections among people that consumes products through Internet appears as an extremely useful asset in order to study emergent properties related to social behavior. This knowledge could be useful, for example, to improve the performance of personal recommendation algorithms. In this contribution, we analyzed five-year records of movie-rating transactions provided by Netflix, a movie rental platform where users rate movies from an online catalog. This dataset can be studied as a bipartite user-item network whose structure evolves in time. Even though several topological properties from subsets of this bipartite network have been reported with a model that combines random and preferential attachment mechanisms [Beguerisse Díaz et al., 2010], there are still many aspects worth to be explored, as they are connected to relevant phenomena underlying the evolution of the network. In this work, we test the hypothesis that bursty human behavior is essential in order to describe how a bipartite user-item network evolves in time. To that end, we propose a novel model that combines, for user nodes, a network growth prescription based on a preferential attachment mechanism acting not only in the topological domain (i.e. based on node degrees) but also in time domain. In the case of items, the model mixes degree preferential attachment and random selection. With these ingredients, the model is not only able to reproduce the asymptotic degree distribution, but also shows an excellent agreement with the Netflix data in several time-dependent topological properties.

Horizontal visibility graphs generated by type-I intermittency

The type-I intermittency route to (or out of) chaos is investigated within the horizontal visibility (HV) graph theory. For that purpose, we address the trajectories generated by unimodal maps close to an inverse tangent bifurcation and construct their associatedHVgraphs.We showhowthe alternation of laminar episodes and chaotic bursts imprints a fingerprint in the resulting graph structure. Accordingly, we derive a phenomenological theory that predicts quantitative values for several network parameters. In particular, we predict that the characteristic power-law scaling of the mean length of laminar trend sizes is fully inherited by the variance of the graph degree distribution, in good agreement with the numerics. We also report numerical evidence on how the characteristic power-law scaling of the Lyapunov exponent as a function of the distance to the tangent bifurcation is inherited in the graph by an analogous scaling of block entropy functionals defined on the graph. Furthermore, we are able to recast the full set of HV graphs generated by intermittent dynamics into a renormalization-group framework, where the fixed points of its graph-theoretical renormalization-group flow account for the different types of dynamics.We also establish that the nontrivial fixed point of this flow coincides with the tangency condition and that the corresponding invariant graph exhibits extremal entropic properties.

¿Qué función representa mejor la distribución granulométrica de la roca?

Se estudia la capacidad para representar la granulometría de la roca en un amplísimo conjunto de datos granulométricos de roca volada y molida de diferentes orígenes. Se evalúan las funciones de Weibull, Grady, log-normal, log-logística, Gilvarry y sus variedades truncadas y bimodales; las distribuciones Swebrec de tres y cinco parámetros también se estudian. La distribución de Weibull es la mejor de las de dos parámetros en cuanto a coeficiente de determinación; entre las truncadas de tres parámetros, Swebrec y Weibull lideran, e igualmente lo hacen sus variedades bimodales de cinco parámetros. Las distribuciones truncadas de tres parámetros superan a sus correspondientes bimodales de cinco parámetros (excepto la Swebrec ampliada, ella misma truncada) en el ajuste de la zona gruesa y también se comportan muy bien en la zona central si bien en esta zona ya algunas bimodales son mejores. En general, las distribuciones de Weibull, Swebrec y Grady son las mejores truncadas. En los finos, las truncadas son aún aceptables aunque pueden esperarse errores altos (por ejemplo del 100 %) mientras que las mejores bimodales (Swebrec ampliada y Weibull) tienen errores máximos generalmente menores de un 30 %. En los muy finos, los errores son casi siempre grandes, si bien moderados con la Swebrec ampliada y, en menor medida, las bimodales Weibull y Grady.

msg1, a novel melanocyte-specific gene, encodes a nuclear protein and is associated with pigmentation.

Messenger RNA transcripts of the highly pigmented murine melanoma B16-F1 cells were compared with those from their weakly pigmented derivative B16-F10 cells by differential display. A novel gene called msg1 (melanocyte-specific gene) was found to be expressed at high levels in B16-F1 cells but at low levels in B16-F10 cells. Expression of msg1 was undetectable in the amelanotic K1735 murine melanoma cells. The pigmented murine melanocyte cell line melan-a expressed msg1, as did pigmented primary cultures of murine and human melanocytes; however, seven amelanotic or very weakly pigmented human melanoma cell lines were negative. Transformation of murine melanocytes by transfection with v-Ha-ras or Ela was accompanied by depigmentation and led to complete loss of msg1 expression. The normal tissue distribution of msg1 mRNA transcripts in adult mice was confined to melanocytes and testis. Murine msg1 and human MSG1 genes encode a predicted protein of 27 kDa with 75% overall amino acid identity and 96% identity within the C-terminal acidic domain of 54 amino acids. This C-terminal domain was conserved with 76% amino acid identity in another protein product of a novel human gene, MRG1 (msg1-related gene), isolated from normal human melanocyte cDNA by 5'-rapid amplification of cDNA ends based on the homology to msg1. The msg1 protein was localized to the melanocyte nucleus by immunofluorescence cytochemistry. We conclude that msg1 encodes a nuclear protein, is melanocyte-specific, and appears to be lost in depigmented melanoma cells.

Record of undergraduates’ activities in virtual learning environments

Virtual learning environments (VLEs) have witnessed a high evolution, namely regarding their potentialities, the tools and the activities they provide. VLEs enable us to access large quantities of data resulting from both students and teachers’ activities developed in those environments. Monitoring undergraduates’ activities in VLEs is important as it allows us to showcase, in a structured way, a number of indicators which may be taken into account to understand the learning process more deeply and to propose improvements in the teaching and learning strategies as well as in the institution’s virtual environment. Although VLEs provide several data sectorial statistics, they do not provide knowledge regarding the institution’s evolution. Therefore, we consider the analysis of the activity logs in VLEs over a period of five years to be paramount. This paper focuses on the analysis of the activities developed by students in a virtual learning environment, from a sample of undergraduate students, approximately 7000 per year, over a period of five academic years, namely from 2009/2010 to 2013/2014. The main aims of this research work are to assess the evolution of activity logs in the virtual learning environment of a Portuguese public higher education institution, in order to fill possible gaps and to hold out the prospect of new forms of use of the environment. The results obtained from the data analysis show that overall, the number of accesses to the virtual learning environment increased over the five years under study. The most used tools were Resources, Messages and Assignments. The most frequent activities developed with these tools were respectively consulting information, sending messages and submitting assignments. The frequency of accesses to the virtual learning environment was characterized according to the number of accesses in the activity log. The data distribution was divided into five frequency categories named very low, low, moderate, high and very high, determined by the percentiles 20, 40, 60, 80 and 100, respectively. The study of activity logs of virtual learning environments is important not only because they provide real knowledge of the use that undergraduates make of these environments, but also because of the possibilities they create regarding the identification of a need for new pedagogical approaches or a reinforcement of previously consolidated approaches.

(Table 1) Crystal sizes of measured samples

Due to experimental difficulties grain size distributions of gas hydrate crystallites are largely unknown in natural samples. For the first time, we were able to determine grain size distributions of six natural gas hydrates for samples retrieved from the Gulf of Mexico and from Hydrate Ridge offshore Oregon from varying depths. High-energy synchrotron radiation provides high photon fluxes as well as high penetration depth and thus allows for investigation of bulk sediment samples. The gas hydrate crystallites appear to be (log-) normally distributed in the natural samples and to be of roughly globular shape. The mean grain sizes are in the range from 300-600 µm with a tendency for bigger grains to occur in greater depth, possibly indicating a difference in the formation age. Laboratory produced methane hydrate, starting from ice and aged for 3 weeks, shows half a log-normal curve with a mean value of ~40 µm. This one order-of-magnitude smaller grain sizes suggests that care must be taken when transposing grain-size sensitive (petro-)physical data from laboratory-made gas hydrates to natural settings.