Orientation of framboidal pyrite in shale

Ordered framboids from Devonian Chattanooga Shale (U.S.A.) and Rammelsberg Banderz (Germany) show a common orientation in any one sample. This observation was made using a stereographic method of reconstruction in which the lineations within the framboids were measured on each of three planes cut mutually at right angles from the rock samples. The explanation for this preferred orientation is not yet known, but it may originate from crystal-growth during compaction of the shales.

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Zusammenfassung Pyrit-Himbeeren aus dem devonischen Chattanooga Shale (U.S.A.) und vom Rammelsberg Banderz zeigen bevorzugte Orientierungen ihrer inneren Struktur (Figure I) gegenüber der Sedimentschichtung. Diese Beobachtungen sind in stereographischen Projektionen aufgezeichnet. Der Vorgang der Orientierung mag auf die Kristallisation der Pyrit-Netzwerke während der Diagenese zurückzuführen sein.

     

Geostatistical integration of gravity and magnetotelluric data to enhance resolution of geologic structure

To enhance the spatial resolution, two types of complementary integration methods were developed using gravity and magnetotelluric (MT) data. The first method involves the enhancement processing of gravity vertical resolution using MT data. This is called a layer density correction (LDC) process which makes the density distribution more sensitive to geologic structure. The second method involves the spatial expansion processing of MT data using the enhanced gravity data. In this process, non-linear indicator transformation (NLIT) and simple kriging with varying local means (SKlm) methods were employed. The assumptions are that while the results are analyzed by different physical properties, each method senses the same underlying geologic structure and thus there is a relationship among the physical properties. The proposed geostatistical integration methods were tested using synthetic models and field data. The experiment illustrates that the integration method proposed in this study can provide improved structures. The method integrates constructively the gravity information having a wider spatial distribution and the MT information having higher vertical resolution.     

Evaluation of seismic behaviour of Cheomseongdae using dynamic centrifuge model test

Cheomseongdae is known to be the oldest astronomical observatory in Asia. According to historical records, the Gyeongju area, where Cheomseongdae is located, suffered from numerous medium‐scale earthquakes. Cheomseongdae has a masonry structure, which is apparently vulnerable to horizontal dynamic loads such as earthquakes. However, despite its appearance, features such as the filler of the lower half, inner irregular‐shaped stones which can induce high frictional resistance, eight long horizontal tie stones inside the artefact, and a grid of interlocking headstones increase its resistance to horizontal dynamic loads. Dynamic centrifuge model tests were performed on Cheomseongdae in order to evaluate the seismic response characteristics of this architectural heritage structure. Model tests were executed on two 1/15‐scale models: one which was an exact duplicate of the original Cheomseongdae and the other without the long horizontal tie stones and grid of interlocking headstones. On the basis of the amplification patterns in the time and frequency domains, the differences in seismic behaviour between the two Cheomseongdae models, and a broken stone at the 19th layer during tests, the long horizontal tie stones and headstones were found to increase the seismic resistance within Cheomseongdae and provide a glimpse of the ‘seismic design’ of our ancestors. Copyright © 2014 John Wiley & Sons, Ltd.     

LH-moment estimation of Wakeby distribution with hydrological applications

This article discusses the method of higher-order L-moment (LH-moment) estimation for the Wakeby distribution (WAD), and describes and formulates details of parameter estimation using LH-moments for WAD. Monte Carlo simulation is performed, to illustrate the performance of the LH-moment method via heavy-tail quantiles (over all quantiles) using WAD. The LH-moment method proves as useful and effective as the L-moment approach in handling data that follow WAD, and it is then applied to annual maximum flood and wave height data.     

Characterizing the effect of heavy metal contamination on marine mussels using metabolomics

Marine mussels (Mytilus) are widely used as bioindicators to measure pollution in marine environments. In this study, (1)H NMR spectroscopy and multivariate statistical analyses were used to differentiate mussel groups from a heavy metal-polluted area (Onsan Bay) and a clean area (Dokdo area). Principal component analysis and orthogonal projection to latent structure-discriminant analysis revealed significant separation between extracts of mussels from Onsan Bay and from the Dokdo area. Organic osmolytes (betaine and taurine) and free amino acids (alanine, arginine, glutamine, phenylalanine, and threonine) were more highly accumulated in Onsan Bay mussels compared with Dokdo mussels. These results demonstrate that NMR-based metabolomics can be used as an efficient method for characterizing heavy metal contamination derived from polluted area compared to clean area and to identify metabolites related to environments that are contaminated with heavy metals.     

Copepod feeding in a coastal area of active tidal mixing: diel and monthly variations of grazing impacts on phytoplankton biomass

This study examined monthly feeding rates and grazing impact on phytoplankton biomass, as well as diel feeding rhythms of four key copepod species in a tidally well mixed estuary (Asan Bay, Korean Peninsula). Monthly ingestion rates estimated based on gut pigment analysis were closely associated with their peak densities, but not with phytoplankton biomass, implying high ingestion may be related to reproductive output for population growth. The three smaller copepods, Acartia hongi, Acartia pacifica and Paracalanus parvus, showed feeding preference for smaller phytoplankton (<20 μm) with higher clearance rates, whereas the larger Calanus sinicus preferred larger phytoplankton. Acartia pacifica and P. parvus showed distinct increased nocturnal feeding rates as measured with gut fluorescence, whereas A. hongi showed no significant day–night differences. Copepod diel feeding patterns were not associated with food quantity, and endogenous physiological rhythm might be hypothesized as responsible for the observed diel feeding patterns. Grazing impact on phytoplankton biomass by the four copepods in the estuary was on average 8% (range 0.2–29.8%) of the phytoplankton standing stock, similar to values reported in other coastal waters. Very high copepod abundances but low daily carbon ration (<20% for all copepods) provided by feeding on phytoplankton indicate that copepods also grazed on other non‐phytoplankton foods in Asan Bay.     

Accounting for high-order correlations in probabilistic characterization of environmental variables,and evaluation

Probabilistic characterization of environmental variables or data typically involves distributional fitting. Correlations, when present in variables or data, can considerably complicate the fitting process. In this work, effects of high-order correlations on distributional fitting were examined, and how they are technically accounted for was described using two multi-dimensional formulation methods: maximum entropy (ME) and Koehler–Symanowski (KS). The ME method formulates a least-biased distribution by maximizing its entropy, and the KS method uses a formulation that conserves specified marginal distributions. Two bivariate environmental data sets, ambient particulate matter and water quality, were chosen for illustration and discussion. Three metrics (log-likelihood function, root-mean-square error, and bivariate Kolmogorov–Smirnov statistic) were used to evaluate distributional fit. Bootstrap confidence intervals were also employed to help inspect the degree of agreement between distributional and sample moments. It is shown that both methods are capable of fitting the data well and have the potential for practical use. The KS distributions were found to be of good quality, and using the maximum likelihood method for the parameter estimation of a KS distribution is computationally efficient.