Molecular expression of opsin gene in growing juvenile mackerel (<Emphasis Type="Italic">Scomber japonicus</Emphasis> Houttuyn)

Fish have developed color vision that is closely adapted to their photic environments, where both spectral sensitivity and the number of visual opsins are influenced. The mackerel used in this study is one of the most important fishery stocks in Korea. The opsin gene of the mackerel juveniles after 20 days in hatching was isolated and characterized based on the molecular study of visual photoreceptor. The full-length mackerel opsin gene was obtained by PCR amplification of genomic DNA, as well as cDNA synthesis. Sequence analysis of the opsin gene showed that it contained a 1,080 bp open reading frame encoding 360 amino acids. Based on Schiff’s base formation (S114, K119), glycosylation (E3, F37) and palmitoylation (S281, 282), the deduced amino acid sequence had a typical rod opsin. The mackerel and Gempylus serpens showed 73.7% DNA homology on opsin gene, which was higher than any other of investigated species. In the analysis of phylogenetic relationship, the genetic placement of the mackerel is closer to that of Scombroidei than Labroidei, with supporting somewhat strong bootstrap value. In the analysis of Northern and RT-PCR, the probed products were observed only in rapidly growing juveniles. These findings indicate that in mackerel opsin mRNA expression can be detected in day-20 hatching larvae. It may play an important role in stimulating growth hormone.     

Fracture strength of dry silicate rocks at high confining pressures and activity of acoustic emission

Three dry silicate rocks, gabbro, dunite and eclogite, were triaxially compressed up to a confining pressure of 3 GPa at room temperature. These rocks exhibited brittle fracture behavior up to the highest confining pressure. The change of the mechanism of fracture in the brittle region is suggested from the measurement of the compressive fracture strength and the activity of acoustic emission. The existence of the “high-pressure brittle-fracture” phase is proposed. The fracture strength increased with increase of confining pressure. The increasing rate of strength was lowered at a value of confining pressure: at about 0.8 GPa on gabbro; at about 1.0 GPa on dunite; and at about 1.5 GPa on eclogite. At lower confining pressures than the above value, the acoustic emission rate began to increase at the onset of dilatancy and increased rapidly followed by fracture as the axial stress was increased. At the higher confining pressures, however, the acoustic emission rate did not increase rapidly before final fracture, and stayed constant to the fracture. The similar behavior was shown on the granite studied previously. It is interesting that the frictional strength forms the boundary between “low- and high-pressure brittle-fracture” phases.     

Improvement of spatial interpolation accuracy of daily maximum air temperature in urban areas using a stacking ensemble technique

ABSTRACT

The reliable and robust monitoring of air temperature distribution is essential for urban thermal environmental analysis. In this study, a stacking ensemble model consisting of multi-linear regression (MLR), support vector regression (SVR), and random forest (RF) optimized by the SVR is proposed to interpolate the daily maximum air temperature (T_max) during summertime in a mega urban area. A total of 10 geographic variables, including the clear-sky averaged land surface temperature and the normalized difference vegetation index, were used as input variables. The stacking model was compared to Cokriging, three individual data-driven methods, and a simple average ensemble model, all through leave-one-station-out cross validation. The stacking model showed the best performance by improving the generalizability of the individual models and mitigating the sensitivity to the extreme daily T_max. This study demonstrates that the stacking ensemble method can improve the accuracy of spatial interpolation of environmental variables in various research fields.     

Effect of spatial variability of cross‐correlated soil properties on bearing capacity of strip footing

Geotechnical engineering problems are characterized by many sources of uncertainty. Some of these sources are connected to the uncertainties of soil properties involved in the analysis. In this paper, a numerical procedure for a probabilistic analysis that considers the spatial variability of cross‐correlated soil properties is presented and applied to study the bearing capacity of spatially random soil with different autocorrelation distances in the vertical and horizontal directions. The approach integrates a commercial finite difference method and random field theory into the framework of a probabilistic analysis. Two‐dimensional cross‐correlated non‐Gaussian random fields are generated based on a Karhunen–Loève expansion in a manner consistent with a specified marginal distribution function, an autocorrelation function, and cross‐correlation coefficients. A Monte Carlo simulation is then used to determine the statistical response based on the random fields. A series of analyses was performed to study the effects of uncertainty due to the spatial heterogeneity on the bearing capacity of a rough strip footing. The simulations provide insight into the application of uncertainty treatment to geotechnical problems and show the importance of the spatial variability of soil properties with regard to the outcome of a probabilistic assessment. Copyright © 2009 John Wiley & Sons, Ltd.     

Geostatistical integration using 2-D electrical resistivity and 3-D gravity methods for detecting cavities in a karst area

Two-dimensional (2-D) electrical resistivity and three-dimensional (3-D) gravity explorations were undertaken to estimate the 3-D distribution of karst cavities at the area of Yongweol-ri in Korea where ground subsidence has occurred. Although the gravity method is a low-cost way of analyzing a 3-D continuous structure, its vertical resolving power is poor. In contrast, the electrical resistivity method can provide a 2-D and/or 3-D subsurface structure with a much higher lateral and vertical resolution than the gravity method. Accordingly, geostatistical methods and density information were used to enhance the 2-D resistivity structure revealed by the electrical resistivity method into a 3-D structure. The assumptions are, first, that each data set senses the same underlying geological structure in terms of different material properties and, secondly, that two different material properties are correlated locally or globally throughout the entire target area. As a result, the distribution of limestone cavities can be estimated under the assumption that they are mostly filled with groundwater and clayey soils and have abnormally low levels of resistivity and density. The estimated distribution corresponds with the grouting, borehole imaging and monitoring data. In this example, it can be seen that the integration analysis of 2-D electrical resistivity and 3-D gravity methods is a very powerful tool for 3-D subsurface imaging and that the method can provide enhanced imaging capabilities for 3-D cavities.     

Tagging-the-triangle algorithm for partitioning features with inconsistent boundaries

In spatial data sets, gaps or overlaps among features are frequently found in spatial tessellations due to the non-abutting edges with adjacent features. These non-abutting edges in loose tessellations are also called inconsistent boundaries or slivers; polygons containing at least one inconsistent boundary are called inconsistent polygons or sliver polygons. The existing algorithms to solve topological inconsistencies in sliver polygons suffer from one or more of three major issues, namely determination of tolerances, excessive CPU processing time for large data sets and loss of vertex history. In this article, we introduce a new algorithm that mitigates these three issues. Our algorithm efficiently searches the features with inconsistent polygons in a given spatial data set and logically partitions them among adjacent features. The proposed algorithm employs the constrained Delaunay triangulation technique to generate labelled triangles from which inconsistent polygons with gaps and overlaps are identified using label counts. These inconsistent polygons are then partitioned using the straight skeleton method. Moreover, each of these partitioned gaps or overlaps is distributed among the adjacent features to improve the topological consistency of the spatial data sets. We experimentally verified our algorithm using the real land cadastre data set. The comparison results show that the proposed algorithm is four times faster than the existing algorithm for data sets with 200,000 edges.     

The effect of the wintertime Arctic Oscillation on springtime vegetation over the northern high latitude region

The winter Arctic Oscillation (AO), a major source of climate variability in the Northern Hemisphere, affects winter and the subsequent spring climate over northern high latitude. Such effects are evident even in the 1st eigenmode of the normalized difference vegetation index (NDVI). The impacts of the winter AO is a dipole pattern between Eurasia and North America; positive (negative) values of the winter AO induce warmer (cooler) and high (low) vegetation activity in the following spring over Eurasia (North America). Regarding the time-lagged response of vegetation, the sea surface temperature (SST) and snow cover contribute to maintaining the large-scale circulation anomaly associated with the AO.     

Effects of biochar, cow bone, and eggshell on Pb availability to maize in contaminated soil irrigated with saline water

Toxicity of heavy metals adversely affects environment and human health. Organic materials derived from natural matters or wastes have been applied to soils to reduce the mobility of contaminants such as heavy metals. However, the application of cow bone powder (CB), biochar (BC), and eggshell powder (ES) is rarely investigated for the reduction of Pb bioavailability in soils irrigated with saline water. The objective of this study was to assess the effectiveness of CB, BC, and ES additions as immobilizing substances on Pb bioavailability in shooting range soil irrigated with deionized and saline water. Each additive of CB, BC, and ES at 5 % (w/w) was mixed with soils and then the deionized and saline water were irrigated for 21 days. With deionized water irrigation, the soils treated with CB, BC, and ES exhibited higher pH when compared with saline water irrigation. With saline water irrigation, the electrical conductivity, water-soluble anions, and cations were significantly increased in soils treated with CB, BC, and ES. The water-soluble Pb in soils treated with CB, BC, and ES was significantly decreased with saline water irrigation. On the other hand, the water-soluble Pb in soil treated with CB was increased with deionized water irrigation. Only BC with saline water irrigation decreased the Pb concentration in maize shoots.     

Satellite-based assessment of large-scale land cover change in Asian arid regions in the period of 2001–2009

Arid regions in Asia are commonly characterized by rapidly growing populations with limited land resources and varying rainfall frequencies under climatic change. Despite being one of the most important environmental challenges in Asia, the changing aridity in this region, particularly due to large-scale land cover change, has not been well documented. In this study, we used rainfall data and a new land heterogeneity index to identify recent trend in land cover changes in the Asian arid regions. The result indicates a significant decreasing trend of barren lands and an increasing trend of vegetated lands. Although the potential land cover change is commonly believed to be strongly sensitive to rainfall change, such sensitivity has not been observed during the nine-year period (2001–2009) analyzed. Through the analyses of two separate periods (2001–2005 and 2005–2009), the sensitivity of rainfall to land cover change in arid regions is found to be dependent on the initial spatial heterogeneity of vegetated land cover. The approach used and the findings in this study represent an important step toward better understanding of large-scale land cover change in the Asian arid regions, and have the potential to predict future land cover change under various climate change scenarios.     

Characterization of Effective Parameters in Abrasive Waterjet Rock Cutting

The rock cutting performance of an abrasive waterjet is affected by various parameters. In this study, rock cutting tests are conducted with different energy (i.e., water pressure, traverse speed, and abrasive feed rate), geometry (i.e., standoff distance), and material parameters [i.e., uniaxial compressive strength (UCS)]. In particular, experimental tests are carried out at a long standoff distance (up to 60 cm) to consider field application. The effective parameters of the rock cutting process are identified based on the relationships between the cutting performance indices (depth, width, and volume) and parameters. In addition, the cutting efficiency is analyzed with effective parameters as well as different pump types and the number of cutting passes considering the concept of kinetic jet energy. Efficiency analysis reveals that the cutting depth efficiency tends to increase with an increase in the water pressure and traverse speed and with a decrease in the standoff distance and UCS. Cutting volume efficiency strongly depends on standoff distance. High efficiency of cutting volume is obtained at a long standoff distance regardless of the pump type. The efficiency analysis provides a realistic way to optimize parameters for abrasive waterjet rock excavation.