Log Of Density Research Articles

Hydrogen Evolution Reaction: Log j0 Versus Work Function Φ As Viewed from Transition State Theory As an Eyring Plot

In 1972, Trasatti correlated the log of the exchange current density (j0) for the hydrogen evolution reaction (HER) with the work functions of 31 metal electrodes to yield two parallel regression lines. [1] The lines are separated by Δ log j0 = 3. Thermodynamically, work function 𝚽 is the energy to remove an electron from a metal to infinity. Perhaps counterintuitively, platinum group metals (PGMs) with the highest 𝚽 sustain the highest j0 values.The elementary, interfacial electron transfer occurs between the electrode and adsorbed hydrogen cation and adsorbed hydrogen atom.H+ ads + e ⇌ H● ads A materials dependent rate expression is developed as follows. [2]The properties of the metal are introduced explicitly into reaction mechanism, characterized by M(e) and M(0), the metal electrode with and without the electron.M(e) + H+ ads ⇄ M(0) + H● ads Classical transition state theory (TST) characterizes the free energy of activation ΔG‡ as the energy difference between the transition state (TS) and the minimum energy of the reactants. The TS forms at equilibrium, where adsorbed hydrogen and metal electrode share the electron.M(e) + H+ ads ⇌ [M ●●● e ●●● Hads]‡ ⇌ M(0) + H● ads Electrochemical potentials set the energy difference in the products and reactant, which sets ΔG‡. Chemical potential (𝞵) difference for the metal without and with the electron define 𝚽. F𝚽 = 𝞵M(0) - 𝞵M(e) F𝚽 is further defined as a chemical free energy that that lowers ΔG‡. F𝚽 is a material specific property that is atypically specified in the rate equation. Because log j0 ∝ - ΔG‡, and chemical free energy F𝚽 lowers ΔG‡, log j0 ∝ F𝚽. Thus, j0 increases exponentially with F𝚽, so PGMs with highest 𝚽 sustain highest j0. Further, the rate expression embeds material specific property 𝚽.The classical Eyring perspective for generic rate constant k’ is k’ = A’ exp[-ΔG‡/RT]. Rate constant is typically determined by varying temperature in a plot of ln k’ versus T-1, where ln k’ = ln A’ - ΔG‡/RT. For isothermal measurements, log j0 is linear with 𝚽 because F𝚽 is a term ΔG‡ chem that is a component in the total ΔG‡. For metals, where 𝚽 > 0, F𝚽 always lowers ΔG‡ for HER; the total activation energy is lowered in proportion to F𝚽. The slopes of log j0 versus 𝚽 is proportional to 𝝰𝚽F𝚽/2.303, where partition coefficient 𝝰𝚽 characterizes ∂ΔG‡/∂𝚽. For the parallel lines in Trasatti’s plot, 𝝰𝚽 = 0.38. The intercepts are independent of 𝚽.The material specific rate expressions derived from classical TST and electrochemical potentials may provide guidance on design of electrocatalysts and provide a path to integration of classical and contemporary modeling of important reaction processes such as HER.

Passive-Sampler-Derived PCB and OCP Concentrations in the Waters of the World─First Results from the AQUA-GAPS/MONET Network.

Persistent organic pollutants (POPs) are recognized as pollutants of global concern, but so far, information on the trends of legacy POPs in the waters of the world has been missing due to logistical, analytical, and financial reasons. Passive samplers have emerged as an attractive alternative to active water sampling methods as they accumulate POPs, represent time-weighted average concentrations, and can easily be shipped and deployed. As part of the AQUA-GAPS/MONET, passive samplers were deployed at 40 globally distributed sites between 2016 and 2020, for a total of 21 freshwater and 40 marine deployments. Results from silicone passive samplers showed α-hexachlorocyclohexane (HCH) and γ-HCH displaying the greatest concentrations in the northern latitudes/Arctic Ocean, in stark contrast to the more persistent penta (PeCB)- and hexachlorobenzene (HCB), which approached equilibrium across sampling sites. Geospatial patterns of polychlorinated biphenyl (PCB) aqueous concentrations closely matched original estimates of production and use, implying limited global transport. Positive correlations between log-transformed concentrations of Σ7PCB, ΣDDTs, Σendosulfan, and Σchlordane, but not ΣHCH, and the log of population density (p < 0.05) within 5 and 10 km of the sampling sites also supported limited transport from used sites. These results help to understand the extent of global distribution, and eventually time-trends, of organic pollutants in aquatic systems, such as across freshwaters and oceans. Future deployments will aim to establish time-trends at selected sites while adding to the geographical coverage.

Ionization Distributions in Outflows of Active Galaxies: Universal Trends and Prospect of Future XRISM Observations

The physics behind the ionization structure of outflows from black holes is yet to be fully understood. Using archival observations with the Chandra/HETG gratings over the past two decades, we measured an absorption measure distribution for a sample of outflows in nine active galactic nuclei (AGNs), namely the dependence of outflow column density, N H, on the ionization parameter, ξ. The slope of N H versus is found to be between 0.00 and 0.72. We find an anticorrelation between the log of total column density of the outflow and the log of AGN luminosity, and none with the black hole mass and accretion efficiency. A major improvement in the diagnostics of AGN outflows will potentially occur with the launch of the XRISM/Resolve spectrometer. We study the ability of Resolve to reveal the outflow ionization structure by constructing the absorption measure distribution from simulated Resolve spectra, utilizing its superior resolution and effective area. Resolve constrains the column density as well as HETG, but with much shorter observations.

Correlation between cumulative mammographic density and age-specific incidence of breast cancer: A biethnic study in Israel.

Women with the most extensive breast density, have a 4- to 6-fold higher cancer risk than women with the lowest density. This cross-sectional study evaluated associations of cumulative mammographic density in two distinct ethnic groups with the respective age-specific breast cancer incidences in the population. The study compared four cohorts of 200 women each aged 35 to 49 and 50 to 74, representing Jewish and Arab ethnicity. Breast density measures were calculated from screening mammograms, using a thresholding software (Cumulus). Breast cancer specific incidence values were obtained from the National Cancer Registry. The percent mammographic density was lower for women aged 50 to 74 than 35 to 49 years, both for Jews: 11.7 vs 23.1 and for Arabs: 11.6 vs 18.3. In contrast, the cumulative density increased with age, from 37.30 to 181.24 in Jews, compared to 21.26 to 108.03 in Arabs. Similar trends in breast cancer incidence rates per 100 000 in the Israeli population were apparent, with an increase from 92.95 to 381.91 in Jews, compared to 48.6 to 244.44 in Arabs. Comparing cumulative density of the cohort with respective age-specific breast cancer incidence in the population yielded a highly significant correlation: Jews; r=.97, P < .0001 and Arabs: r=.86, P=.007. A strong association was found between the log of cumulative density and the log of cancer incidence, as well. Our study identified correlations between cumulative mammographic density and breast cancer incidence in two distinct populations. The findings should prompt research to enhance our understanding of the pathogenesis of breast cancer, and lead to novel insights into measures of prevention.

Long-term Trend in Mean Density of Antarctic Krill (Euphausia superba) Uncertain

Two recent attempts to model the long-term trend in mean density of Antarctic krill in the southwestern sector of the Atlantic using the KRILLBASE dataset using different statistical methods as well as inclusion versus exclusion of data from “non-scientific” nets have resulted in disparate conclusions. The approach that used a linear mixed model (LMM) fitted to the log of mean density, after standardisation was applied to individual net hauls and with means calculated for 12 spatial strata by years between 1976 and 2016, gave a highly statistically significant linear “regional” decline north of 60oS and, to a lesser degree, south of this latitude. The alternative approach that used a ”hurdle” model fitted to the individual net haul data, excluded regional stratification, and excluded non-scientific nets failed to detect an overall significant decline. The method of modelling log transformed means was reappraised and corrected by applying a meta-analytic LMM approach. Additionally, nonlinear smooths in year by region and a smooth in mean “climatological temperature” were included in the LMM. This model showed on average a mostly consistent decline north of 60oS, however, neither trend was significantly different from a no-trend prediction with the trend north of 60oS highly uncertain. Uncertainty of predictions resulted in only weak power to detect a substantial decline of the order of 70% between 1985 and 2005. These model-based inferences neither strongly support nor reject a general hypothesis that there has been a dramatic decline in density of Antarctic krill in the Southwest Atlantic over this period.

Application of LithoScanner Logging Technology in CO2 Geological Storage Injection Well

The formation evaluation in a primary formation of a CO2 sequestration project in Western Australia has been very challenging due to the presence of glauconite and other iron rich minerals. The conventional method cannot handle the mineralogy effects, hence the accurate porosity, clay type and clay content cannot be calculated accurately. The latest generation in spectroscopy technology LithoScanner was brought to the project and run in well A for the first time in Australia. The tool has a high output pulse neutron generator and unique cerium-doped lanthanum bromide (LaBr3:Cr) gamma ray detector. This combination enables the tool to measure both inelastic and capture spectra for an expanded set of elements from that of previous-generation tools. We are measuring elements that make up more than 99% of the average abundance in the earth’s crust. Measuring the elements is the starting point to calculate minerals, matrix density and those are key to obtain accurate reserves estimates (porosity) and build an accurate petrophysical and reservoir model. For well A, the LithoScanner elements weight fractions are used in the Techlog QuantiElan module to solve mineralogy that includes quartz, K-feldspar, calcite, siderite, pyrite, illite, kaolinite, glauconite and chlorite. There is a very good agreement between the computed mineralogy and the mineralogy from core measurements. LithoScanner provides a continuous log of matrix density that is used as an input to porosity calculations. This formation evaluation based on Litho Scanner does not require the subjective inputs from the log analysis, but completely rely on the tool’s reading. It can be used for both simple and complex formation to obtain the good consistency and accurate answers.

Optimising sampling strategies for emergency response: Soil sampling

The novel approach for optimising soil sampling strategies in areas affected by radionuclides is suggested. Major factors influencing the efficiency of soil sampling strategies, including (number of samples, sampling area size, sampling depth and spatial resolution of the sample sites are examined to provide optimisation of the soil sampling plan. The experimental field studies to validate the suggested approach were performed in 25 sampling units ranging from 1.2 × 1.2 m to 60 × 60 m size. The sampling units were selected on arable farmlands, natural meadow and former agricultural land), as well as coniferous and deciduous forests with contamination density of 137Cs ranging from 2.8 kBq·m−2 to 24.5 MBq·m−2. The studied areas were contaminated by both the global fallout and the Chernobyl radioactive particles of different types. To determine the values of standard deviation of the log of the soil contamination density of 137Cs, 25 to 256 soil samples were collected with an increment of 0.07–10 m within each sampling unit. It was found that the values of standard deviation of the log of the soil contamination density of 137Cs were not dependent on the mean contamination density, the type of radioactive deposition and the landscape features. The mean value of standard deviation calculated for all sites studied was estimated as 0.44 ± 0.15 and 0.30 ± 0.10 for the sampling area 0.001 m2 (∅37 mm) and 0.005 m2 (∅80 mm) at the relative measurement uncertainties lower than 10% (CI = 95%). Concentrations of 137Cs in the soil samples were statistically independent when sampling points were situated at a distance larger than 1 m one from each other. A simple method was developed for assessing minimum sample sizes required for estimation of the median or the geometric mean of radionuclide soil contamination with a relative uncertainty set by the user. The approach was also suggested for estimation of the uncertainty of soil contamination for the case of composite samples. The approach was implemented in the Ukrainian national requirements for assessment of quality of the soil.

Spectral edge behavior for eventually monotone Jacobi and Verblunsky coefficients

We consider Jacobi matrices with eventually increasing sequences of diagonal and off-diagonal Jacobi parameters. We describe the asymptotic behavior of the subordinate solution at the top of the essential spectrum, and the asymptotic behavior of the spectral density at the top of the essential spectrum. In particular, allowing on both diagonal and off-diagonal Jacobi parameters perturbations of the free case of the form - \sum_{j=1}^J c_j n^{-\tau_j} + o(n^{-\tau_1-1}) with 0 &lt; \tau_1 &lt; \tau_2 &lt; \dots &lt; \tau_J and c_1 &gt; 0 , we find the asymptotic behavior of the log of spectral density to order O(\mathrm {log}(2-x)) as x approaches 2. Apart from its intrinsic interest, the above results also allow us to describe the asymptotics of the spectral density for orthogonal polynomials on the unit circle with real-valued Verblunsky coefficients of the same form.

Erratum

Previous article FreeErratumOriginal articleDefining freshwater mussel mesohabitat associations in an alluvial, Coastal Plain riverPDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinked InRedditEmailQR Code SectionsMoreIn the article by Smit and Kaiser, published in the December 2016 issue of Freshwater Science (35:1276–1290), the original Fig. 4 (on page 1284) contained y values of the natural log of total mussel density, whereas the y-axis label suggested values of log base 10. The figure was corrected to contain y values of log base 10 to agree with the y-axis label. The authors regret the error.Figure 4. Box-and-whisker plots illustrating the distribution of total density of mussels collected within each of the 5 mesohabitat classes. Lines in boxes are medians, box ends are quartiles, and whiskers show ranges. Boxes with the same letters are not significantly different. IRZ = inner recirculation zone, MC = mid channel, ORZ = outer recirculation zone, PB = point bar, and POB = pool/outer bend.View Large ImageDownload PowerPoint Previous article DetailsFiguresReferencesCited by Freshwater Science Volume 38, Number 1March 2019 Published on behalf of the Society for Freshwater Science Article DOIhttps://doi.org/10.1086/703247 © 2019 by The Society for Freshwater Science.PDF download Crossref reports no articles citing this article.Related articlesDefining freshwater mussel mesohabitat associations in an alluvial, Coastal Plain river15 Sep 2016Freshwater Science

Impact of additive covariate error on linear model

We consider effect of additive covariate error on linear model in observational (radiation epidemiology) study for exposure risk. Additive dose error affects dose-response shape under general linear regression settings covering identity-link GLM type models and linear excess-relative-risk grouped-Poisson models. Under independent error, dose distribution that log of dose density is up to quadratic polynomial on an interval (the log-quadratic density condition), normal, exponential, and uniform distributions, is the condition for linear regression calibration. Violation of the condition can result low-dose-high-sensitivity model from linear no-threshold (LNT) model by the dose error. Power density is also considered. A published example is given.

Bayesian time series regression with nonparametric modeling of autocorrelation

Series models have several functions: comprehending the functional dependence of variable of interest on covariates, forecasting the dependent variable for future values of covariates and estimating variance disintegration, co-integration and steady-state relations. Although the regression function in a time series model has been extensively modeled both parametrically and nonparametrically, modeling of the error autocorrelation is mainly restricted to the parametric setup. A proper modeling of autocorrelation not only helps to reduce the bias in regression function estimate, but also enriches forecasting via a better forecast of the error term. In this article, we present a nonparametric modeling of autocorrelation function under a Bayesian framework. Moving into the frequency domain from the time domain, we introduce a Gaussian process prior to the log of the spectral density, which is then updated by using a Whittle approximation for the likelihood function (Whittle likelihood). The posterior computation is simplified due to the fact that Whittle likelihood is approximated by the likelihood of a normal mixture distribution with log-spectral density as a location shift parameter, where the mixture is of only five components with known means, variances, and mixture probabilities. The problem then becomes conjugate conditional on the mixture components, and a Gibbs sampler is used to initiate the unknown mixture components as latent variables. We present a simulation study for performance comparison, and apply our method to the two real data examples.

Bacillus Cereus Biodegradability of Phosphorus and other Heavy Metals in Nigeria’s Agbaja Iron Ore

An investigation into the capacity of Bacillus cereus to degrade some of the heavy metals found in Nigeria’s Agbaja iron ore was carried out in the laboratory for 10 weeks. As obtained iron ore from Agbaja community in Kogi State of Nigeria was crushed and sieved to select 0.50/0.25mm particle size. Bacillus cereus was one of the microorganisms identified after culturing a portion of the crushed iron ore in suitable media overtime. Some control samples were also set up that did not contain either the microbes and/or ore samples. At weekly interval, samples were removed and analyzed to obtain ammonium phospho-molybdate precipitate which was titrated with 0.1 N-HCl to determine the amount of phosphorus (P). Liquid samples were analyzed for heavy metals concentration using UniCam Solaar 969 AA spectrophotometer. Findings reveal that the microbes degraded 58.18% P and in the process accumulated some of the heavy metals: 82.17% Cu, 100% Cd and Fe, 8.12% Zn and 68.42% Pb. The pH of the media remained entirely basic attaining 9.63 at the end of the investigation. The log of microbial density which maximized in the 3rd week at 7.498 cfu/ml (colony forming unit/milliliter) showed serious decline by the 10th week to 4.763 cfu/ml. It is possible the microorganisms may have had a low degradation capacity as a result of heavy metals over-accumulation, especially that of Pb, known to be highly poisonous above certain concentrations. Recommendations include a further study of the broth media mixture with samples and microorganisms as findings may enhance an efficient metabolic wastes management and a sustainable microbial degradation of iron ore samples.

Bacillus Cereus Biodegradability of Phosphorus and other Heavy Metals in Nigeria’s Agbaja Iron Ore

An investigation into the capacity of Bacillus cereus to degrade some of the heavy metals found in Nigeria’s Agbaja iron ore was carried out in the laboratory for 10 weeks. As obtained iron ore from Agbaja community in Kogi State of Nigeria was crushed and sieved to select 0.50/0.25mm particle size. Bacillus cereus was one of the microorganisms identified after culturing a portion of the crushed iron ore in suitable media overtime. Some control samples were also set up that did not contain either the microbes and/or ore samples. At weekly interval, samples were removed and analyzed to obtain ammonium phospho-molybdate precipitate which was titrated with 0.1 N-HCl to determine the amount of phosphorus (P). Liquid samples were analyzed for heavy metals concentration using UniCam Solaar 969 AA spectrophotometer. Findings reveal that the microbes degraded 58.18% P and in the process accumulated some of the heavy metals: 82.17% Cu, 100% Cd and Fe, 8.12% Zn and 68.42% Pb. The pH of the media remained entirely basic attaining 9.63 at the end of the investigation. The log of microbial density which maximized in the 3rd week at 7.498 cfu/ml (colony forming unit/milliliter) showed serious decline by the 10th week to 4.763 cfu/ml. It is possible the microorganisms may have had a low degradation capacity as a result of heavy metals over-accumulation, especially that of Pb, known to be highly poisonous above certain concentrations. Recommendations include a further study of the broth media mixture with samples and microorganisms as findings may enhance an efficient metabolic wastes management and a sustainable microbial degradation of iron ore samples.

Determinants of the Transmission Variation of Hand, Foot and Mouth Disease in China.

Severe outbreaks of hand, foot and mouth disease (HFMD) have occurred in China for decades. Our understanding of the HFMD transmission process and its determinants is still limited. In this paper, factors that affect the local variation of HFMD transmission process were studied. Three classes of factors, including meteorological, demographic and public health intervention factors, were carefully selected and their effects on HFMD transmission were investigated with Pearson’s correlation coefficient and multiple linear regression models. The determining factors for the variation of HFMD transmission were different for the southeastern and the northwestern regions of China. In the northwest, fadeouts occurred yearly, and the average age at infection and the fadeout were negatively correlated with the population density. In the southeast, HFMD transmission was governed by the combined effects of the birth rate, the relative humidity and the interaction of the Health System Performance and the log of the population density. When the Health System Performance was low, HFMD transmission increased with the population density, but when the Health System Performance was high, the better health performance counteracted the transmission increase due to the higher population density.

First report of Phytophthora sojae causing root rot in soybean [Glycine max (L.) Merr.] in Alberta, Canada

Soybean [Glycine max (L.) Merr.] has great potential as an alternative crop in western Canada. Root rot is a common constraint in soybean production, and the occurrence of root rot was documented in all 29 fields surveyed in southern Alberta in 2014. Phytophthora spp. cause seed rot, pre- and post-emergence damping-off, and stem and root rot wherever soybean is produced, but it has not been previously reported in association with soybean in Alberta. Following a survey of soybean fields in 2014, root tissue with typical symptoms of root rot was plated onto a selective growth medium, and two isolates were designated as putative Phytophthora spp. based on their colony characteristics. These two isolates were homothallic on lima bean agar, producing smooth, thick-walled oospores and mostly paragynous with some amphigynous antheridia. Based on these criteria, the two isolates were identified as Phytophthora sojae Kaufmann & Gerdemann. Sequencing of the internal transcribed spacer (ITS) region revealed 100% identity with ITS sequences of P. sojae available in GenBank. A pathogenicity test revealed that both isolates of P. sojae were able to cause root rot on soybean and produce typical chocolate brown stem lesions just above the base of the plants. The two isolates were classified as races 4 and 28 of P. sojae based on their virulence on a set of soybean differential cultivars. Race 28 was more virulent than race 4 on the soybean cultivars ‘XBP27005’ and ‘XBP29002’. Regression analysis showed the positive linear relationships of the log of inoculum density with disease severity, and negative linear relationships with seedling emergence, plant height, and plant biomass. This is the first report of Phytophthora spp. causing root rot in soybean in Alberta.

Effect of Electric Field Strength on Cell Morphology and Anion Incorporation of Anodic Porous Alumina

Anodic porous alumina film, a typical self-ordered nanohole material formed by anodizing aluminum in an appropriate acidic solution, is a promising candidate for starting materials of nanofabrication of various devices. Investigations concerning the cell dimensions of porous anodic alumina films have been extensively performed after the confirmation of the classical cell model proposed by Keller et al (1). It was suggested in these studies that cell dimensions, such as pore and cell diameters and barrier layer thickness, primarily depended on the formation voltage, and that they increased linearly with increasing voltage (2). Nevertheless, the importance of current density as a controlling factor of the cell geometry was sometime claimed (3, 4). According to the classical theory of ionic conduction at the high field strength for the anodic barrier film grown on various metals (5, 6), the film thickness of each metal is inversely proportional to the logarithm of ionic current when the film is formed up to the same voltage. Thus, it is indicated that the log of current density I is proportional to the electric field strength E, i.e., the formation voltage / film thickness ratio at the barrier layer, as we reported previously (7). Concerning the anion incorporation into the film, we found that anion content was also proportional to the electric field strength E, i.e., the log of current density i (7). This principal is suggested to be applicable to porous anodic films. The purpose of the present study is the confirmation of the effect of electric field strength as a controlling factor of the cell morphology of porous anodic alumina such as pore diameter / cell diameter ratio that affects to the radius of curvature of cell base pattern and porosity. In addition, effect of electric field strength on incorporation behavior of electrolyte anions into cell wall has been studied. Obtained knowledge could help us to get further insight into self-ordering mechanism of anodic porous alumina. Although pore and cell sizes of the films formed in oxalic acid were larger than those formed in sulfuric acid even at the same voltages, the ratio of cell diameter to pore diameter (dcell / d pore) of both films is in a linear relation with the logarithm of current density (log i). The electric field strength across the barrier layer of porous films varies linearly with the logarithm of current density as in the case of barrier type films. Therefore, dcell / d pore ratio is regarded to be proportional to the electric field strength. From these results, it is deduced that pore diameter is proportional to voltage and inversely propor­tional to the square of the electric field strength, whereas barrier layer thickness and cell diameter are proportional to voltage and inversely proportional to the electric field strength. Accordingly, pore diameter is more strongly affected by current density than other cell parameters are. The content of incorporated anion in the films increases linearly with increasing log i, hence electric field strength. Therefore, it is evident that the anion incorporation is exactly governed by the electric field strength. [1] F.Keller, M.S.Hunter and D.L.Robinson, This Journal, 100, 411 (1953). [2] J.P.O'Sullivan and G.C.Wood, Proc. Roy. Soc. Lond. A.317, 511 (1970). [3] K.V.Heber, Electrochim. Acta, 23, 127 (1978). [4] S. Ono, M. Saito, M. Ishiguro and H. Asoh, J. Electrochem. Soc ., 151, B473 (2004). [5] N. Cabrera and N. F. Mott, Ret. Pror. Phys., 12, 163 (1948). [6] C. J. Dell’Oca and L. Young, J. Electrochem. Soc., 117, 1548 (1970). [7] S. Ono, F. Mizutani, M. Ue, and N. Masuko, PV 2001-22, p.1129, The Electrochemical Society Proceedings Series, Pennington, NJ (2001).

First report of Fusarium proliferatum causing root rot in soybean (Glycine max L.) in Canada

Soybean plants showing symptoms of root rot were collected from fields in western Canada to determine the etiology of the disease. Four Fusarium spp., Fusarium avenaceum, Fusarium culmorum, Fusarium oxysporum and Fusarium proliferatum, were identified based on their cultural and morphological characteristics. All of the isolates of these species were pathogenic on soybean. Identification of F. proliferatum was confirmed by PCR analysis with the F. proliferatum-specific primer set CLPRO1/CLPRO2. Amplicons of the target fragments (partial calmodulin (cld) gene, 526 bp) were obtained only from DNA of isolates tentatively identified as F. proliferatum, and sequencing of the amplicon showed it shared 100% identity with the cld gene sequences of F. proliferatum in GenBank. F. proliferatum was the most aggressive of the four Fusarium species identified, causing the greatest root rot severity and reduction of seedling emergence. F. avenaceum was the second most aggressive and caused a greater reduction in seedling numbers than F. culmorum or F. oxysporum. Correlation analysis showed that seedling emergence, shoot dry weight, and seed yield decreased, and root rot severity increased, with the log of inoculum density of F. proliferatum. This is the first report of F. proliferatum causing soybean root rot in Canada.

A Function Accounting for Training Set Size and Marker Density to Model the Average Accuracy of Genomic Prediction

Prediction of genomic breeding values is of major practical relevance in dairy cattle breeding. Deterministic equations have been suggested to predict the accuracy of genomic breeding values in a given design which are based on training set size, reliability of phenotypes, and the number of independent chromosome segments (). The aim of our study was to find a general deterministic equation for the average accuracy of genomic breeding values that also accounts for marker density and can be fitted empirically. Two data sets of 5′698 Holstein Friesian bulls genotyped with 50 K SNPs and 1′332 Brown Swiss bulls genotyped with 50 K SNPs and imputed to ∼600 K SNPs were available. Different k-fold (k = 2–10, 15, 20) cross-validation scenarios (50 replicates, random assignment) were performed using a genomic BLUP approach. A maximum likelihood approach was used to estimate the parameters of different prediction equations. The highest likelihood was obtained when using a modified form of the deterministic equation of Daetwyler et al. (2010), augmented by a weighting factor (w) based on the assumption that the maximum achievable accuracy is . The proportion of genetic variance captured by the complete SNP sets () was 0.76 to 0.82 for Holstein Friesian and 0.72 to 0.75 for Brown Swiss. When modifying the number of SNPs, w was found to be proportional to the log of the marker density up to a limit which is population and trait specific and was found to be reached with ∼20′000 SNPs in the Brown Swiss population studied.

Large-scale depositional characteristics of the Ulleung Basin and its impact on electrical resistivity and Archie-parameters for gas hydrate saturation estimates

Gas hydrate saturation estimates were obtained from an Archie-analysis of the Logging-While-Drilling (LWD) electrical resistivity logs under consideration of the regional geological framework of sediment deposition in the Ulleung Basin, East Sea, of Korea. Porosity was determined from the LWD bulk density log and core-derived values of grain density. In situ measurements of pore-fluid salinity as well as formation temperature define a background trend for pore-fluid resistivity at each drill site. The LWD data were used to define sets of empirical Archie-constants for different depth-intervals of the logged borehole at all sites drilled during the second Ulleung Basin Gas Hydrate Drilling Expedition (UBGH2). A clustering of data with distinctly different trend-lines is evident in the cross-plot of porosity and formation factor for all sites drilled during UBGH2. The reason for the clustering is related to the difference between hemipelagic sediments (mostly covering the top ∼100 mbsf) and mass-transport deposits (MTD) and/or the occurrence of biogenic opal. For sites located in the north-eastern portion of the Ulleung Basin a set of individual Archie-parameters for a shallow depth interval (hemipelagic) and a deeper MTD zone was achieved. The deeper zone shows typically higher resistivities for the same range of porosities seen in the upper zone, reflecting a shift in sediment properties. The presence of large amounts of biogenic opal (up to and often over 50% as defined by XRD data) was especially observed at Sites UBGH2-2_1 and UBGH2-2_2 (as well as UBGH1-9 from a previous drilling expedition in 2007). The boundary between these two zones can also easily be identified in gamma-ray logs, which also show unusually low readings in the opal-rich interval. Only by incorporating different Archie-parameters for the different zones a reasonable estimate of gas hydrate saturation was achieved that also matches results from other techniques such as pore-fluid freshening, velocity-based calculations, and pressure-core degassing experiments. Seismically, individual boundaries between zones were determined using a grid of regional 2D seismic data. Zoning from the Archie-analysis for sites in the south-western portion of the Ulleung Basin was also observed, but at these sites it is linked to individually stacked MTDs only and does not reflect a mineralogical occurrence of biogenic opal or hemipelagic sedimentation. The individual MTD events represent differently compacted material often associated with a strong decrease in porosity (and increase in density), warranting a separate set of empirical Archie-parameters.

Split Hamiltonian Monte Carlo

We show how the Hamiltonian Monte Carlo algorithm can sometimes be speeded up by “splitting” the Hamiltonian in a way that allows much of the movement around the state space to be done at low computational cost. One context where this is possible is when the log density of the distribution of interest (the potential energy function) can be written as the log of a Gaussian density, which is a quadratic function, plus a slowly-varying function. Hamiltonian dynamics for quadratic energy functions can be analytically solved. With the splitting technique, only the slowly-varying part of the energy needs to be handled numerically, and this can be done with a larger stepsize (and hence fewer steps) than would be necessary with a direct simulation of the dynamics. Another context where splitting helps is when the most important terms of the potential energy function and its gradient can be evaluated quickly, with only a slowly-varying part requiring costly computations. With splitting, the quick portion can be handled with a small stepsize, while the costly portion uses a larger stepsize. We show that both of these splitting approaches can reduce the computational cost of sampling from the posterior distribution for a logistic regression model, using either a Gaussian approximation centered on the posterior mode, or a Hamiltonian split into a term that depends on only a small number of critical cases, and another term that involves the larger number of cases whose influence on the posterior distribution is small.