Pore size distributions derived from adsorption isotherms, immersion calorimetry, and isosteric heats: A comparative study

We compare the pore size distribution of a well-characterized activated carbon derived from model-dependent, adsorption integral equation (AIE) methods with those from model-independent, immersion calorimetry and isosteric heat analyses. The AIE approach applied to nitrogen gave a mean pore width of 0.57 nm; the CO2 distribution exhibited wider dispersion. Spherical model application to CO2 and diffusion limitations for nitrogen and argon were proposed as primary reasons for inconsistency. Immersion enthalpy revealed a sharp decrease in available area equivalent to a cut-off due to molecular exclusion when the accessible surface was assessed against probe kinetic diameter. Mean pore width was identified as 0.58 ± 0.02 nm, endorsing the underlying assumptions for the nitrogen-based AIE approach. A comparison of the zero-coverage isosteric heat of adsorption for various non-polar adsorptives by the porous test sample was compared with the same adsorptives in contact with a non-porous reference adsorbent, leading to an energy ratio or adsorption enhancement factor. A linear relationship between the energy ratio and probe kinetic diameter indicated a primary pore size at 0.59 nm. The advantage of this enthalpy, model-independent methods over AIE were due to no assumptions regarding probe molecular shape, and no assumptions for pore shape and/or connectivity.

¬FISH DISTRIBUTIONS IN LAKE ONTARIO’S EASTERN BASIN AND THE UPPER ST. LAWRENCE RIVER: AN ANALYSIS USING GIS AND OCCUPANCY MODELLING TECHNIQUES

Predictive models of species distributions are important tools for fisheries management. Unfortunately, these predictive models can be difficult to perform on large waterbodies where fish are difficult to detect and exhaustive sampling is not possible. In recent years the development of Geographic Information Systems (GIS) and new occupancy modelling techniques has improved our ability to predict distributions across landscapes as well as account for imperfect detection. I surveyed the nearshore fish community at 105 sites between Kingston, Ontario and Rockport, Ontario with the objective of modelling geographic and environmental characteristics associated with littoral fish distributions. Occupancy modelling was performed on Round Goby, Yellow perch, and Lepomis spp. Modelling with geographic and environmental covariates revealed the effect of shoreline exposure on nearshore habitat characteristics and the occupancy of Round Goby. Yellow Perch, and Lepomis spp. occupancy was most strongly associated negatively with distance to a wetland. These results are consistent with past research on large lake systems indicate the importance of wetlands and shoreline exposure in determining the fish community of the littoral zone. By examining 3 species with varying rates of occupancy and detection, this study was also able to demonstrate the variable utility of occupancy modelling.

An alternative methodology for fitting selectivity curves to pre-defined distributions

A non-linear least-squares methodology for simultaneously estimating parameters of selectivity curves with a pre-defined functional form, across size classes and mesh sizes, using catch size frequency distributions, was developed based on the model of Kirkwood and Walker [Kirkwood, G.P., Walker, T.L, 1986. Gill net selectivities for gummy shark, Mustelus antarcticus Gunther, taken in south-eastern Australian waters. Aust. J. Mar. Freshw. Res. 37, 689-697] and [Wulff, A., 1986. Mathematical model for selectivity of gill nets. Arch. Fish Wiss. 37, 101-106]. Observed catches of fish of size class I in mesh m are modeled as a function of the estimated numbers of fish of that size class in the population and the corresponding selectivities. A comparison was made with the maximum likelihood methodology of [Kirkwood, G.P., Walker, T.I., 1986. Gill net selectivities for gummy shark, Mustelus antarcticus Gunther, taken in south-eastern Australian waters. Aust. J. Mar. Freshw. Res. 37, 689-697] and [Wulff, A., 1986. Mathematical model for selectivity of gill nets. Arch. Fish Wiss; 37, 101-106], using simulated catch data with known selectivity curve parameters, and two published data sets. The estimated parameters and selectivity curves were generally consistent for both methods, with smaller standard errors for parameters estimated by non-linear least-squares. The proposed methodology is a useful and accessible alternative which can be used to model selectivity in situations where the parameters of a pre-defined model can be assumed to be functions of gear size; facilitating statistical evaluation of different models and of goodness of fit. (C) 1998 Elsevier Science B.V.

Use of Coarse-resolution models of species' distributions to guide local conservation inferences

Distribution models are used increasingly for species conservation assessments over extensive areas, but the spatial resolution of the modeled data and, consequently, of the predictions generated directly from these models are usually too coarse for local conservation applications. Comprehensive distribution data at finer spatial resolution, however, require a level of sampling that is impractical for most species and regions. Models can be downscaled to predict distribution at finer resolutions, but this increases uncertainty because the predictive ability of models is not necessarily consistent beyond their original scale. We analyzed the performance of downscaled, previously published models of environmental favorability (a generalized linear modeling technique) for a restricted endemic insectivore, the Iberian desman (Galemys pyrenaicus), and a more widespread carnivore, the Eurasian otter ( Lutra lutra), in the Iberian Peninsula. The models, built from presence–absence data at 10 × 10 km resolution, were extrapolated to a resolution 100 times finer (1 × 1 km). We compared downscaled predictions of environmental quality for the two species with published data on local observations and on important conservation sites proposed by experts. Predictions were significantly related to observed presence or absence of species and to expert selection of sampling sites and important conservation sites. Our results suggest the potential usefulness of downscaled projections of environmental quality as a proxy for expensive and time-consuming field studies when the field studies are not feasible. This method may be valid for other similar species if coarse-resolution distribution data are available to define high-quality areas at a scale that is practical for the application of concrete conservation measures

Distinguishing the distributions of two cryptic frogs (Anura: Discoglossidae) using molecular data and environmental modeling

Currently, the identification of two cryptic Iberian amphibians, Discoglossus galganoi Capula, Nascetti, Lanza, Bullini and Crespo, 1985 and Discoglossus jeanneae Busack, 1986, relies on molecular characterization. To provide a means to discern the distributions of these species, we used 385-base-pair sequences of the cytochrome b gene to identify 54 Spanish populations of Discoglossus. These data and a series of environmental variables were used to build up a logistic regression model capable of probabilistically designating a specimen of Discoglossus found in any Universal Transverse Mercator (UTM) grid cell of 10 km × 10 km to one of the two species. Western longitudes, wide river basins, and semipermeable (mainly siliceous) and sandstone substrates favored the presence of D. galganoi, while eastern longitudes, mountainous areas, severe floodings, and impermeable (mainly clay) or basic (limestone and gypsum) substrates favored D. jeanneae. Fifteen percent of the UTM cells were predicted to be shared by both species, whereas 51% were clearly in favor of D. galganoi and 34% were in favor of D. jeanneae, considering odds of 4:1. These results suggest that these two species have parapatric distributions and allow for preliminary identification of potential secondary contact areas. The method applied here can be generalized and used for other geographic problems posed by cryptic species.

Convergence time to equilibrium distributions of autonomous and periodic non-autonomous graphs

We present some estimates of the time of convergence to the equilibrium distribution in autonomous and periodic non-autonomous graphs, with ergodic stochastic adjacency matrices, using the eigenvalues of these matrices. On this way we generalize previous results from several authors, that only considered reversible matrices.

How well can models predict changes in species distributions? A 13-year-old otter model revisited

Species distribution and ecological niche models are increasingly used in biodiversity management and conservation. However, one thing that is important but rarely done is to follow up on the predictive performance of these models over time, to check if their predictions are fulfilled and maintain accuracy, or if they apply only to the set in which they were produced. In 2003, a distribution model of the Eurasian otter (Lutra lutra) in Spain was published, based on the results of a country-wide otter survey published in 1998. This model was built with logistic regression of otter presence-absence in UTM 10 km2 cells on a diverse set of environmental, human and spatial variables, selected according to statistical criteria. Here we evaluate this model against the results of the most recent otter survey, carried out a decade later and after a significant expansion of the otter distribution area in this country. Despite the time elapsed and the evident changes in this species’ distribution, the model maintained a good predictive capacity, considering both discrimination and calibration measures. Otter distribution did not expand randomly or simply towards vicinity areas,m but specifically towards the areas predicted as most favourable by the model based on data from 10 years before. This corroborates the utility of predictive distribution models, at least in the medium term and when they are made with robust methods and relevant predictor variables.

Temperature-averaged and total free-free Gaunt factors for κ and Maxwellian distributions of electrons

Aims. Optically thin plasmas may deviate from thermal equilibrium and thus, electrons (and ions) are no longer described by the Maxwellian distribution. Instead they can be described by κ-distributions. The free-free spectrum and radiative losses depend on the temperature-averaged (over the electrons distribution) and total Gaunt factors, respectively. Thus, there is a need to calculate and make available these factors to be used by any software that deals with plasma emission. Methods. We recalculated the free-free Gaunt factor for a wide range of energies and frequencies using hypergeometric functions of complex arguments and the Clenshaw recurrence formula technique combined with approximations whenever the difference between the initial and final electron energies is smaller than 10−10 in units of z2Ry. We used double and quadruple precisions. The temperature- averaged and total Gaunt factors calculations make use of the Gauss-Laguerre integration with 128 nodes. Results. The temperature-averaged and total Gaunt factors depend on the κ parameter, which shows increasing deviations (with respect to the results obtained with the use of the Maxwellian distribution) with decreasing κ. Tables of these Gaunt factors are provided.

Shaping transverse beam distributions by means of adiabatic crossing of resonances

Non-linear effects are responsible for peculiar phenomena in charged particles dynamics in circular accelerators. Recently, they have been used to propose novel beam manipulations where one can modify the transverse beam distribution in a controlled way, to fulfil the constraints posed by new applications. One example is the resonant beam splitting used at CERN for the Multi-Turn Extraction (MTE), to transfer proton beams from PS to SPS. The theoretical description of these effects relies on the formulation of the particle's dynamics in terms of Hamiltonian systems and symplectic maps, and on the theory of adiabatic invariance and resonant separatrix crossing. Close to resonance, new stable regions and new separatrices appear in the phase space. As non-linear effects do not preserve the Courant-Snyder invariant, it is possible for a particle to cross a separatrix, changing the value of its adiabatic invariant. This process opens the path to new beam manipulations. This thesis deals with various possible effects that can be used to shape the transverse beam dynamics, using 2D and 4D models of particles' motion. We show the possibility of splitting a beam using a resonant external exciter, or combining its action with MTE-like tune modulation close to resonance. Non-linear effects can also be used to cool a beam acting on its transverse beam distribution. We discuss the case of an annular beam distribution, showing that emittance can be reduced modulating amplitude and frequency of a resonant oscillating dipole. We then consider 4D models where, close to resonance, motion in the two transverse planes is coupled. This is exploited to operate on the transverse emittances with a 2D resonance crossing. Depending on the resonance, the result is an emittance exchange between the two planes, or an emittance sharing. These phenomena are described and understood in terms of adiabatic invariance theory.

Modelling and classification with quantile-based distributions

In this work, we explore and demonstrate the potential for modeling and classification using quantile-based distributions, which are random variables defined by their quantile function. In the first part we formalize a least squares estimation framework for the class of linear quantile functions, leading to unbiased and asymptotically normal estimators. Among the distributions with a linear quantile function, we focus on the flattened generalized logistic distribution (fgld), which offers a wide range of distributional shapes. A novel naïve-Bayes classifier is proposed that utilizes the fgld estimated via least squares, and through simulations and applications, we demonstrate its competitiveness against state-of-the-art alternatives. In the second part we consider the Bayesian estimation of quantile-based distributions. We introduce a factor model with independent latent variables, which are distributed according to the fgld. Similar to the independent factor analysis model, this approach accommodates flexible factor distributions while using fewer parameters. The model is presented within a Bayesian framework, an MCMC algorithm for its estimation is developed, and its effectiveness is illustrated with data coming from the European Social Survey. The third part focuses on depth functions, which extend the concept of quantiles to multivariate data by imposing a center-outward ordering in the multivariate space. We investigate the recently introduced integrated rank-weighted (IRW) depth function, which is based on the distribution of random spherical projections of the multivariate data. This depth function proves to be computationally efficient and to increase its flexibility we propose different methods to explicitly model the projected univariate distributions. Its usefulness is shown in classification tasks: the maximum depth classifier based on the IRW depth is proven to be asymptotically optimal under certain conditions, and classifiers based on the IRW depth are shown to perform well in simulated and real data experiments.

Mechanical Properties And Fracture Dynamics Of Silicene Membranes.

As graphene has become one of the most important materials, there is renewed interest in other similar structures. One example is silicene, the silicon analogue of graphene. It shares some of the remarkable graphene properties, such as the Dirac cone, but presents some distinct ones, such as a pronounced structural buckling. We have investigated, through density functional based tight-binding (DFTB), as well as reactive molecular dynamics (using ReaxFF), the mechanical properties of suspended single-layer silicene. We calculated the elastic constants, analyzed the fracture patterns and edge reconstructions. We also addressed the stress distributions, unbuckling mechanisms and the fracture dependence on the temperature. We analysed the differences due to distinct edge morphologies, namely zigzag and armchair.

Measurement Of Longitudinal Spin Asymmetries For Weak Boson Production In Polarized Proton-proton Collisions At Rhic.

We report measurements of single- and double-spin asymmetries for W^{±} and Z/γ^{*} boson production in longitudinally polarized p+p collisions at sqrt[s]=510  GeV by the STAR experiment at RHIC. The asymmetries for W^{±} were measured as a function of the decay lepton pseudorapidity, which provides a theoretically clean probe of the proton's polarized quark distributions at the scale of the W mass. The results are compared to theoretical predictions, constrained by polarized deep inelastic scattering measurements, and show a preference for a sizable, positive up antiquark polarization in the range 0.05

[the New Classification Of Breast Cancers: Finding The Luminal A].

To compare the distributions of patients with clinical-pathological subtypes of luminal B-like breast cancer according to the 2011 and 2013 St. Gallen International Breast Cancer Conference Expert Panel. We studied 142 women with breast cancer who were positive to estrogen receptor and had been treated in São Paulo state, southeast Brazil. The expression of the following receptors was assessed by immunohistochemistry: estrogen, progesterone (PR) and Ki-67. The expression of HER-2 was measured by fluorescent in situ hybridization analysis in tissue microarray. There were 29 cases of luminal A breast cancers according to the 2011 St. Gallen International Breast Cancer Conference Expert Panel that were classified as luminal B-like in the 2013 version. Among the 65 luminal B-like breast cancer cases, 29 (45%) were previous luminal A tumors, 15 cases (20%) had a Ki-67 >14% and were at least 20% PR positive and 21 cases (35%) had Ki-67 >14% and more than 20% were PR positive. The 2013 St. Gallen consensus updated the definition of intrinsic molecular subtypes and increased the number of patients classified as having luminal B-like breast cancer in our series, for whom the use of cytotoxic drugs will probably be proposed with additional treatment cost.

On The Consistency Of Monte Carlo Track Structure Dna Damage Simulations.

Monte Carlo track structures (MCTS) simulations have been recognized as useful tools for radiobiological modeling. However, the authors noticed several issues regarding the consistency of reported data. Therefore, in this work, they analyze the impact of various user defined parameters on simulated direct DNA damage yields. In addition, they draw attention to discrepancies in published literature in DNA strand break (SB) yields and selected methodologies. The MCTS code Geant4-DNA was used to compare radial dose profiles in a nanometer-scale region of interest (ROI) for photon sources of varying sizes and energies. Then, electron tracks of 0.28 keV-220 keV were superimposed on a geometric DNA model composed of 2.7 × 10(6) nucleosomes, and SBs were simulated according to four definitions based on energy deposits or energy transfers in DNA strand targets compared to a threshold energy ETH. The SB frequencies and complexities in nucleosomes as a function of incident electron energies were obtained. SBs were classified into higher order clusters such as single and double strand breaks (SSBs and DSBs) based on inter-SB distances and on the number of affected strands. Comparisons of different nonuniform dose distributions lacking charged particle equilibrium may lead to erroneous conclusions regarding the effect of energy on relative biological effectiveness. The energy transfer-based SB definitions give similar SB yields as the one based on energy deposit when ETH ≈ 10.79 eV, but deviate significantly for higher ETH values. Between 30 and 40 nucleosomes/Gy show at least one SB in the ROI. The number of nucleosomes that present a complex damage pattern of more than 2 SBs and the degree of complexity of the damage in these nucleosomes diminish as the incident electron energy increases. DNA damage classification into SSB and DSB is highly dependent on the definitions of these higher order structures and their implementations. The authors' show that, for the four studied models, different yields are expected by up to 54% for SSBs and by up to 32% for DSBs, as a function of the incident electrons energy and of the models being compared. MCTS simulations allow to compare direct DNA damage types and complexities induced by ionizing radiation. However, simulation results depend to a large degree on user-defined parameters, definitions, and algorithms such as: DNA model, dose distribution, SB definition, and the DNA damage clustering algorithm. These interdependencies should be well controlled during the simulations and explicitly reported when comparing results to experiments or calculations.