The origin and biogeochemistry of organic matter in surface sediments of Lake Shihwa and Lake Hwaong

To understand the origin and biogeochemistry of the organic matter in surface sediments of Lake Shihwa and Lake Hwaong, organic nitrogen, inorganic nitrogen, labile organic carbon, and residual organic carbon contents as well as stable isotope ratios for carbon and nitrogen were determined by KOBr-KOH treatment. Ratios of organic carbon to organic nitrogen (C_org/N_org) (mean = 24) were much higher than ratios of organic carbon to total nitrogen (C_org/N_tot) (mean=12), indicating the presence of significant amounts of inorganic nitrogen in the surface sediments of both lakes. Stable isotope ratios for organic nitrogen were, on average, 5.2‰ heavier than ratios of inorganic nitrogen in Lake Shihwa, but those same ratios were comparable in Lake Hwaong. This might be due to differences in the origin or the degree of degradation of sedimentary organic matter between the two lakes. In addition, stable isotope ratios for labile organic carbon were, on average, 1.4‰ heavier than those for residual organic carbon, reflecting the preferential oxidation of¹³C-enriched organic matter. The present study demonstrates that KOBr-KOH treatment of sedimentary organic matter can provide valuable information for understanding the origin and degradation state of organic matter in marine and brackish sediments. This also suggests that the ratio of C_org/N_org and stable isotope ratios for organic nitrogen can be used as indexes of the degree of degradation of organic matter.     

Landslide susceptibility analysis using GIS and artificial neural network

The purpose of this study is to develop landslide susceptibility analysis techniques using an arti?cial neural network and to apply the newly developed techniques to the study area of Yongin in Korea. Landslide locations were identi?ed in the study area from interpretation of aerial photographs, ?eld survey data, and a spatial database of the topography, soil type and timber cover. The landslide‐related factors (slope, curvature, soil texture, soil drainage, soil effective thickness, timber age, and timber diameter) were extracted from the spatial database. Using those factors, landslide susceptibility was analysed by arti?cial neural network methods. The landslide susceptibility index was calculated by the back‐propagation method, which is a type of arti?cial neural network method, and the susceptibility map was made with a geographic information system (GIS) program. The results of the landslide susceptibility analysis were veri?ed using landslide location data. The validation results showed satisfactory agreement between the susceptibility map and the existing data on landslide location. A GIS was used to ef?ciently analyse the vast amount of data, and an arti?cial neural network to be an effective tool to maintain precision and accuracy. The results can be used to reduce hazards associated with landslides and to plan land use and construction. Copyright © 2003 John Wiley & Sons, Ltd.     

Optimal design of viscoelastic dampers using eigenvalue assignment

In this study a procedure for determining the optimum size and location of viscoelastic dampers is proposed using the eigenvalue assignment technique. Natural frequencies and modal damping ratios, required to realize a given target response, are determined first by the convex model. Then the desired dynamic structural properties are realized by optimally distributing the damping and stiffness coefficients of viscoelastic dampers using non‐linear programming based on the gradient of eigenvalues. This optimization method provides information on the optimal location as well as the magnitude of the damper parameters. The proposed procedure is applied to the retrofit of a 10‐story shear frame, and to a three‐dimensional structure with an asymmetric plan. The analysis results confirm that the responses of model structures retrofitted by the proposed method correspond well with the given target response. Copyright © 2003 John Wiley & Sons, Ltd.     

Determination and application of the weights for landslide susceptibility mapping using an artificial neural network

The purpose of this study is the development, application, and assessment of probability and artificial neural network methods for assessing landslide susceptibility in a chosen study area. As the basic analysis tool, a Geographic Information System (GIS) was used for spatial data management and manipulation. Landslide locations and landslide-related factors such as slope, curvature, soil texture, soil drainage, effective thickness, wood type, and wood diameter were used for analyzing landslide susceptibility. A probability method was used for calculating the rating of the relative importance of each factor class to landslide occurrence. For calculating the weight of the relative importance of each factor to landslide occurrence, an artificial neural network method was developed. Using these methods, the landslide susceptibility index (LSI) was calculated using the rating and weight, and a landslide susceptibility map was produced using the index. The results of the landslide susceptibility analysis, with and without weights, were confirmed from comparison with the landslide location data. The comparison result with weighting was better than the results without weighting. The calculated weight and rating can be used to landslide susceptibility mapping.     

Probabilistic approach for active control of structures: experimental verification

In our previous study (Earthquake Engineering and Structural Dynamics 2003; 32 :2301), we have developed a probabilistic algorithm for active control of structures. In the probabilistic control algorithm, the control force is determined by the probability that the structural energy exceeds a specified target critical energy, and the direction of a control force is determined by the Lyapunov controller design method. In this paper, an experimental verification of the proposed probabilistic control algorithm is presented. A three‐story test structure equipped with an active mass driver (AMD) has been used. The effectiveness of the control algorithm has been examined by exciting the test structure using a sinusoidal signal, a scaled El Centro earthquake and a broadband Gaussian white noise; and, especially, experiments on control have been performed under different conditions to that of system identification in order to prove the stability and robustness of the proposed control algorithm. The experimental results indicate that the probabilistic control algorithm can achieve a significant response reduction under various types of ground excitations even when the modeling error exists. Copyright © 2004 John Wiley & Sons, Ltd.     

Effect of shipping activity on warming trends in the Canadian Arctic

This paper presents a detailed account of the effect of shipping activity on the increasing trends of air temperatures in the Canadian Arctic region for the period of 1980–2018. Increasing trend of temperature has gained significant attention with respect to shipping activities and sea ice area in the Canadian Arctic. Temperature, sea ice area and shipping traffic datasets were investigated, and simple linear regression analyses were conducted to predict the rate of change(per decade) of the average temperature, considering winter(January) and summer(July) seasons. The results indicate that temperature generally increased over the studied region. Significant warming trend was observed during July, with an increase of up to 1℃, for the Canadian Arctic region. Such increasing trend of temperature was observed during July from the lower to higher latitudes. The increase in temperature during July is speculated to increase the melting of ice. Results also show a decline in sea ice area has a significant positive effect on the shipping traffic, and the numbers of marine vessel continue to increase in the region. The increase in temperature causes the breaking of sea ice due to shipping activities over northern Arctic Canada.     

Assessing Winter Wheat Responses to Climate Change Scenarios: A Simulation Study in the U.S. Great Plains

Hard red winter wheat (Triticum aestivum L.) is a major crop in the Great Plains region of the U.S. The goal of this assessment effort was to investigate the influence of two contrasting global climate change projections (U.K. Hadley Center for Climate Prediction and Research and Canadian Centre for Climate Modelling and Analysis) on the yield and percent kernel nitrogen content of winter wheat at three locations in Nebraska. These three locations represent sub-humid and semi arid areas and the transition between these areas and are also representative of major portions of the winter wheat growing areas of the central Great Plains. Climate scenarios based on each of the projections for each location were developed using the LARS-WG weather generator along with data from automated weather stations. CERES-Wheat was used to simulate the responses for two contrasting cultivars of wheat using two sowing dates. The first sowing date represented current sowing dates appropriate for each location. The second sowing date was later and represents the approximate date when the mean air temperature from the climate scenarios is the same as the mean air temperature from the actual climate data at the current sowing dates. The yield and percent kernel nitrogen content using the two climate scenarios generally decrease going from the sub-humid eastern to the semi arid western parts of Nebraska. Results from these simulations indicate that yield and percent kernel nitrogen content using the two climate scenarios could not both be maintained at levels currently simulated. Protein content (directly related to kernel nitrogen content) and end-use quality are the primary determinants for the use of hard red winter wheat in baked goods. Nitrogen management and new cultivars, which can enhance the uptake and translocation of nitrogen, will be proactive steps to meet the challenges of global climate change as represented by these climate scenarios.     

Vertical distribution of giant jellyfish, <Emphasis Type="Italic">Nemopilema nomurai</Emphasis> using acoustics and optics

Nemopilema nomurai jellyfish, which are believed to complete their development in the East China Sea, have started migrating into the Yellow Sea in recent years. We obtained biomass estimates of this species in the Yellow Sea using bottom trawl fishing gear and sighting surveys over a 5-year period. These methods are effective for obtaining N. nomurai jellyfish density estimates and information about the community distribution near the bottom or surface of the sea. To verify the vertical distributions of giant jellyfish between, we used hydroacoustic equipment, including an optical stereo camera system attached to a towed sledge and an echo counting method with scientific echosounder system. Acoustic and optical data were collected while the vessel moved at 3 knots, from which the distribution and density of N. nomurai jellyfish were analyzed. Subsequently, the camera system was towed from a 7 m mean depth to sea level, with the detection range of the acoustic system extending from an 8 m depth to the bottom surface. The optical and acoustic methods indicated the presence of vertical distribution of 0.11³ (inds/m³) and 0.064 (inds/m3), respectively. However, the vertical distribution indicated that around 93% of individuals occurred at a depth range of 10–40 m; thus, a 2.4-fold greater density was estimated by acoustic echo counting compared to the optical method.     

Geotechnical design parameter evaluation using the alluvial plain characteristics in southeastern Iraq

Geotechnical construction is responsible for the overall stability of superstructures, and if there are design errors, the structure will be exposed to potential problems. Geotechnical design starts with the correct interpretation of the target ground. Southeastern Iraq is mainly comprised of an alluvial plain with diverse geological features, and, therefore, geotechnical design requires a detailed interpretation and understanding of the area. This paper reports on laboratory and field tests and in-depth analyses conducted on these alluvial plains. The results reveal that the upper layer of this area is highly over-consolidated. This may have been caused by the removal of overburden pressure as a result of glaciation and desiccation. The highly over-consolidated soils caused considerable sample disturbance by swelling the bored sample; this provided less reliable results. However, the cone penetration test was regarded as the most appropriate field assessment method for deriving sensible geotechnical design parameters. Despite its limitations in clayey soils, the standard penetration test provided results that matched well with previous observations due to the high penetration resistance of the highly over-consolidated ground. Down-hole tests and plate load tests were considered less reliable methods due to their limited applicability in this area. This study considers geographical features, laboratory methods, and empirical correlations from in situ tests, and, therefore, provides a well-summarized guideline to evaluate special geotechnical characteristics of the alluvial plain in southeastern Iraq.