Thermal effects on the growth and fatty acid composition of four harmful algal bloom species: Possible implications for ichthyotoxicity

Little is known regarding how harmful algal bloom species respond to different temperatures in terms of fatty acid production. This study examined the effects of temperature on the growth rates, cell volumes, and fatty acid concentrations and compositions of four harmful algal bloom species (HABs), Akashiwo sanguinea, Alexandrium tamarense, Chattonella ovata, and Prorocentrum minimum. The HABs species were cultured at 15, 20, 25, and 30°C in a nutrient-enriched medium. Three of the species maintained optimal growth rates over a wide range of temperatures, but A. tamarense did not. The cell volumes of each species showed little change over the temperature range. The total fatty acid concentrations in A. sanguinea, A. tamarense and C. ovata decreased as the temperature increased, but P. minimum showed no trend in this respect. Polyunsaturated fatty acids (PUFAs), the key biochemical components that maintain cell membrane fluidity and which are associated with toxicity, decreased in both concentration and proportion of total fatty acids as temperature increased, except in A. sanguinea, in which the proportion of PUFAs to the total fatty acids increased. These reductions in PUFA concentration and proportion could reduce cell membrane fluidity and toxicity in HABs; however, enhanced growth and/or ruptured cells, which are considered more toxic than intact cells, could compensate for the reduced per-cell toxicity. This phenomenon might impact on the marine ecosystem and aquaculture industry.     

Predicting rock size distribution in mine blasting using various novel soft computing models based on meta-heuristics and machine learning algorithms

Blasting is well-known as an effective method for fragmenting or moving rock in open-pit mines. To evaluate the quality of blasting, the size of rock distribution is used as a critical criterion in blasting operations. A high percentage of oversized rocks generated by blasting operations can lead to economic and environmental damage. Therefore, this study proposed four novel intelligent models to predict the size of rock distribution in mine blasting in order to optimize blasting parameters, as well as the efficiency of blasting operation in open mines. Accordingly, a nature-inspired algorithm (i.e., firefly algorithm – FFA) and different machine learning algorithms (i.e., gradient boosting machine (GBM), support vector machine (SVM), Gaussian process (GP), and artificial neural network (ANN)) were combined for this aim, abbreviated as FFA-GBM, FFA-SVM, FFA-GP, and FFA-ANN, respectively. Subsequently, predicted results from the abovementioned models were compared with each other using three statistical indicators (e.g., mean absolute error, root-mean-squared error, and correlation coefficient) and color intensity method. For developing and simulating the size of rock in blasting operations, 136 blasting events with their images were collected and analyzed by the Split-Desktop software. In which, 111 events were randomly selected for the development and optimization of the models. Subsequently, the remaining 25 blasting events were applied to confirm the accuracy of the proposed models. Herein, blast design parameters were regarded as input variables to predict the size of rock in blasting operations. Finally, the obtained results revealed that the FFA is a robust optimization algorithm for estimating rock fragmentation in bench blasting. Among the models developed in this study, FFA-GBM provided the highest accuracy in predicting the size of fragmented rocks. The other techniques (i.e., FFA-SVM, FFA-GP, and FFA-ANN) yielded lower computational stability and efficiency. Hence, the FFA-GBM model can be used as a powerful and precise soft computing tool that can be applied to practical engineering cases aiming to improve the quality of blasting and rock fragmentation.     

Effects of particle shape on the cushioning mechanics of rock-filled gabions

Acta Geotechnica - Rock-filled gabions are commonly installed in front of reinforced concrete structures to reduce concentrated impact loads induced by rock fall and boulders entrained in debris...     

Distribution and Sources of Dissolved and Particulate Heavy Metals (Mn,Co, Ni,Cu, Zn,Cd, Pb) in Masan Bay,Korea

Ocean Science Journal - In this study, we investigated the spatial and temporal distribution and sources of dissolved and particulate heavy metals in Masan Bay, an area that for a long time has...     

Molecular Identification and Expression Analysis of Carbonic Anhydrase VII in Pufferfish (Takifugu rubripes)

Ocean Science Journal - A carbonic anhydrase VII gene, encoding 277 amino acids, was identified in the intestinal tissue of pufferfish (Takifugu rubripes). The translated protein with an 833-bp...     

Quantitative Analysis of Micro-structural Changes in a Bituminous Coal After Exposure to Supercritical CO2 and Water

Natural Resources Research - High-volatile bituminous coal samples were reacted in deionized water with supercritical CO2 (ScCO2–water) under simulated in situ pressure and temperature...     

Underwater autonomous manipulation for intervention missions AUVs

Many underwater intervention tasks are today performed using manned submersibles or remotely operated vehicles in teleoperation mode. Autonomous underwater vehicles are mostly employed in survey applications. In fact, the low bandwidth and significant time delay inherent in acoustic subsea communications represent a considerable obstacle to remotely operate a manipulation system, making it impossible for remote controllers to react to problems in a timely manner.Nevertheless, vehicles with no physical link and with no human occupants permit intervention in dangerous areas, such as in deep ocean, under ice, in missions to retrieve hazardous objects, or in classified areas. The key element in underwater intervention performed with autonomous vehicles is autonomous manipulation. This is a challenging technology milestone, which refers to the capability of a robot system that performs intervention tasks requiring physical contacts with unstructured environments without continuous human supervision.Today, only few AUVs are equipped with manipulators. SAUVIM (Semi Autonomous Underwater Vehicle for Intervention Mission, University of Hawaii) is one of the first underwater vehicle capable of autonomous manipulation.This paper presents the solutions chosen within the development of the system in order to address the problems intrinsic to autonomous underwater manipulation. In the proposed approach, the most noticeable aspect is the increase in the level of information transferred between the system and the human supervisor.We describe one of the first trials of autonomous intervention performed by SAUVIM in the oceanic environment. To the best knowledge of the authors, no sea trials in underwater autonomous manipulation have been presented in the literature. The presented operation is an underwater recovery mission, which consists in a sequence of autonomous tasks finalized to search for the target and to securely hook a cable to it in order to bring the target to the surface.     

Coastal environmental assessment and management by ecological simulation in Yeoja Bay, Korea

An eco-hydrodynamic model was used to estimate the carrying capacity of pollutant loads and response of water quality to environmental change in Yeoja Bay, Korea. An energy-system model also was used to simulate the fluctuation in nutrients and organic matter in the bordering wetland. Most water quality factors showed a pulsed pattern, and the concentrations of nutrients and organic matter of seawater increased when input loads of nutrients increased due to freshwater discharge. The well-developed tidal zones and wetlands in the northern area of the bay were highly sensitive to input loads. Residence times of water, chemical oxygen demand (COD), and dissolved inorganic nitrogen (DIN) within the bay were estimated to be about 16 days, 43.2 days, and 50.2 days, respectively. Water quality reacted more sensitively to the effects of nitrogen and phosphorus input than to COD. A plan to reduce the present levels of COD and dissolved inorganic phosphorus (DIP) by 20–30% and DIN by at least 50% in pollutant loads is needed for satisfying the target water quality criteria. The natural removal rate of nutrients in wetlands by reeds was assessed to be approximately 10%.     

Rare earth elements in bottom sediments of major rivers around the Yellow Sea: implications for sediment provenance

Rare earth elements (REEs) of 91 fine-grained bottom sediment samples from five major rivers in Korea (the Han, Keum, and Yeongsan) and China (the Changjiang and Huanghe) were studied to investigate their potential as source indicator for Yellow Sea shelf sediments, this being the first synthetic report on REE trends for bottom sediments of these rivers. The results show distinct differences in REE contents and their upper continental crust (UCC)-normalized patterns: compared to heavy rare earth elements (HREEs), light rare earth elements (LREEs) are highly enriched in Korean river sediments, in contrast to Chinese river sediments that have a characteristic positive Eu anomaly. This phenomenon is observed also in primary source rocks within the river catchments. This suggests that source rock composition is the primary control on the REE signatures of these river sediments, due largely to variations in the levels of chlorite and monazite, which are more abundant in Korean bottom river sediments. Systematic variations in ΣLREE/ΣHREE ratios, and in (La/Yb)–(Gd/Yb)_UCC but also (La/Lu)–(La/Y)_UCC and (La/Y)–(Gd/Lu)_UCC relations have the greatest discriminatory power. These findings are consistent with, but considerably expand on the limited datasets available to date for suspended sediments. Evidently, the REE fingerprints of these river sediments can serve as a useful diagnostic tool for tracing the provenance of sediments in the Yellow Sea, and for reconstructing their dispersal patterns and the circulation system of the modern shelf, as well as the paleoenvironmental record of this and adjoining marginal seas.     

Numerical simulation of nearshore circulation on field topography under random wave environment

In order to investigate surf zone hydrodynamics through two-dimensional numerical simulations of nearshore circulation under random wave environment, a nearshore circulation model, SHORECIRC, and a random wave model, SWAN, were combined and utilized. Using this combined model, a numerical simulation of the October 2, 1997 SandyDuck field experiment was performed. For this simulation, field topography and an input offshore spectrum were constructed using observed data sets synchronized with the experiment. The wave-breaking model in SWAN was modified by using breaker parameters varied according to bottom slope. The simulation results were compared with the experimental data, which revealed a well-developed longshore current, as well as with results using other combinations which were SHORECIRC and its original monochromatic wave-driver, and SHORECIRC and the default of SWAN. The results from the novel combined model agreed well with the experimental data. The results of the present simulation also indicate that alongshore field topography influences shear fluctuation of longshore currents.