Effects of copper (I) oxide on growth and biochemical compositions of two marine microalgae

In copper based antifouling (AF) paints Cu (I) oxide was largely used as booster biocide. In this study effect of Cu (I) oxide on two marine microalgae, Tetraselmis suecica and Dunaliella tertiolecta was demonstrated. EC50 (96 hr) concentrations estimated for T. suecica and D. tertiolecta were 1.3 mg l(-1) and 1.34 mg l(-1), respectively. Copper (I) oxide induced changes in growth, chlorophyll, carbohydrate and protein contents were observed in T. suecica and D. tertiolecta. At low concentration of 0.0625 mg l(-1), 3-26% and 1-16% growth stimulation was observed in T. suecica and T. tertiolecta respectively. Increasing Cu (I) oxide concentrations proportionately decreased the carbohydrate and protein contents. This study clearly indicates the toxicity of excessive Cu (I) oxide on growth and biochemical compositions of T. suecica and D. tertiolecta.     

Assessment of Flood Vulnerability Based on CMIP5 Climate Projections in South Korea

The objective of this article was to assess flood vulnerability based on the representative concentration pathways (RCP) scenarios at city and county levels. A quantile mapping method was adopted to correct bias that is inherent in climate change scenarios. A series of proxy variables related to climate exposure, sensitivity, and adaptive capacity were chosen to assess flood vulnerability. Proxy variables were standardized using the Z‐score method. Principal component analysis was carried out to calculate the weighting of proxy variables. The study area was the Korean peninsula. The spatial resolution was on a city and county basis and the temporal resolution was 1990s, 2025s, 2055s, and 2085s (divided into 1976‐2005, 2011‐2040, 2041‐2070, and 2071‐2100). In the spatial comparison, we found that the areas with high‐level flood vulnerability increased over time in the central region, including metropolitan areas, and near the southern coast. In the temporal comparison, we found that the RCP4.5 scenario showed a tendency to increase steadily and the RCP8.5 scenario showed a tendency to decrease in the 2055s slightly and increase again in the 2085s. The study findings may provide useful data for the determination of priority for countermeasure development, though robustness of these findings with additional future projections should be established.     

Prioritization of water management for sustainability using hydrologic simulation model and multicriteria decision making techniques

The objective of this study is to develop an alternative evaluation index (AEI) in order to determine the priorities of a range of alternatives using both the hydrological simulation program in FORTRAN (HSPF) and multicriteria decision making (MCDM) techniques. In order to formulate the HSPF model, sensitivity analyses of water quantity (peak discharge and total volume) and quality (BOD peak concentrations and total loads) are conducted and a number of critical parameters were selected. To achieve a more precise simulation, the study watershed is divided into four regions for calibration and verification according to landuse, location, slope, and climate data. All evaluation criteria were selected using the Driver–Pressure–State–Impact–Response (DPSIR) model, a sustainability evaluation concept. The Analytic Hierarchy Process is used to estimate the weights of the criteria and the effects of water quantity and quality were quantified by HSPF simulation. In addition, AEIs that reflected residents' preferences for management objectives are proposed in order to induce the stakeholder to participate in the decision making process.     

Evaluation of a prenatal screening procedure for β-thalassaemia carriers in a chinese populationbased on the mean corpuscular volume (MCV)

Haemoglobin A₂ (HbA₂) levels were determined on 25 β-thalassaemia carriers by the microcolumn method and were found to range from 4.5–7.2 per cent (mean 5.2±0.82 S.D.). The haemoglobin level (Hb), mean corpuscular volume (MCV), plasma ferritin and HbA₂ levels were measured on a further 299 cconsecutive Chinese pregnant women at a gestation of less than 24 weeks. 18 patients (6 per cent) had HbA₂ level greater than 4.5 per cent and were diagnosed to be β-thalassaemic carriers. It was observed that all these patients had a MCV below 75 fl. If this level is selected in a screening procedure based on measurement of MCV alone all β-thalassaemia carriers could be detected and 11 per cent of the population screened would require HbA₂ estimation. At a lower cut-off level of 70 fl, 8 per cent of the population screened wouid require HbA₂ measurement (a decrease of 27 per cent) but the detection rate will be lowered considerably (83 per cent). The high false positive rate at all cut-off levels of MCV was largely due to the prevalence of iron deficiency anaemia in the population. Estimation of plasma ferritin level in patients with low MCV will reduce this false positive rate, but there will be a considerable delay in diagnosis in patients with concomitant iron deficiency and β-thalassaemia. The presence of iron deficiency in β-thalassaemia carriers did not reduce their HbA₂ level below the diagnostic range in this study. Measurement of Hb level did not appear to be useful as a screening method since one third of the β-thalassaemia carriers had a Hb level over 11 g/dl. The validity of the MCV cut-off levels derived from the first part of the study was assessed in screening a larger population. 61 β-thalassaemia carriers (6 per cent) were detected out of 1166 patients screened. This incidence was not significantly different from the first part of the study. All these 61 patients had a MCV less than 75 ml. It was concluded that a two-step screening policy, based on MCV measurement followed by HbA₂ estimation when the MCV value is less than 75 fl, is suitable for our population. It is efficient, straight forward with excellent sensitivity and required less time and effort for both laboratory staff and clinicians.     

Development of intelligent sorting system realized with the aid of laser-induced breakdown spectroscopy and hybrid preprocessing algorithm-based radial basis function neural networks for recycling black plastic wastes

Plastic recycling has been the key issue for reducing environmental problems and resolving resource depletion. To improve the recovery rate of plastics, the plastic wastes are correctly identified according to their resin type. However, the identification system, which is able to identify black plastics according to not only the type of black plastics but also the grade of resins correctly, has not been introduced. In this paper, laser-induced breakdown spectroscopy, intelligent algorithms and preprocessing algorithms are used to improve the identification of black plastics such as polypropylene, polystyrene (PS), and acrylonitrile butadiene styrene (ABS). The laser-induced breakdown spectroscopy is capable of obtaining the characteristic spectrum regardless of material’s physical state. To extract the new features which are very valuable to improving learning performance, increasing computational efficiency, and building better generalization models from the obtained spectra through laser-induced breakdown spectroscopy, the hybrid preprocessing algorithm, composed of principal component analysis and independent component analysis, is used. In addition, the intelligent algorithm named the extended radial basis function neural networks inheriting the advantages of fuzzy theory and neural networks is used to identify black plastic samples into several categories with respect to their resins. The proposed identification system, composed of three parts such as laser induced breakdown spectroscopy, hybrid preprocessing algorithms, and an efficient intelligent classification algorithm, is able to show the synergy effect on the black plastic identification problem. From several experimental results, it can be seen that the identification system based on laser-induced breakdown spectroscopy and the intelligent algorithm is used for identification of black plastics by resin type.     

Decision support for prioritizing energy technologies against high oil prices: A fuzzy analytic hierarchy process approach

To provide national energy security in the 21st century, establishing a long-term strategic energy technology development is essential through selection and specialization. We established a strategic energy technology roadmap (ETRM) taking economic spin-offs, commercial potential, inner capacity, and technical spin-off into account. In this research, we suggest an integrated multi-criteria decision making (MCDM) approach, which is composed of more than two criteria as the assessment of the optimal alternatives and solutions in the real world with the fuzzy theory and analytic hierarchy process (AHP), to prioritize the weights of energy technologies of ETRM as we allocate R&D budget using a fuzzy analytic hierarchy process. Building technology is the most preferred technology in the sector of energy technologies against high oil prices. And the coal technology and transportation technology follows and take the 2nd and 3rd place with the fuzzy AHP approach.     

Revised relative potency values for PCDDs, PCDFs, and non-ortho-substituted PCBs for the optimized H4IIE-luc in vitro bioassay

While the World Health Organization 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) equivalency factors are useful estimates of relative potencies of mixtures when conducting risk assessments, they are not useful when comparing the results of bioassays such as the H4IIE-luc to concentrations of TCDD equivalents calculated from instrumental analyses. Since there are thousands of dioxin-like compounds (DLCs), one use of screening assays is to determine if all of the aryl hydrocarbon receptor (AhR) active DLCs in a mixture have been accounted for in instrumental analyses. For this purpose, bioassay-specific relative potency (ReP) values are needed. RePs of 21 polychlorinated dibenzo-p-dioxins, polychlorinated dibenzofurans, and dioxin-like polychlorinated biphenyls that exhibit effects mediated through the AhR were determined by use of the H4IIE-luc assay. Different values of RePs are derived, depending on the statistical, curve-fitting methods used to derive them from the dose–response relationships. Here, we discuss the various methods for deriving RePs from in vitro data and their assumptions and effects on values of RePs. Full dose–response curves of 2,3,7,8-TCDD and other representative DLCs were used to estimate effective concentrations at multiple points (e.g., EC20-50-80), which were then used to estimate ReP of each DLC to 2,3,7,8-TCDD.     

Transportation noise and exposed population of an urban area in the Republic of Korea

Using noise prediction models, we explored the transportation noise levels of Youngdeungpo-gu, an urbanized area of Seoul Metropolitan City in the Republic of Korea. In addition, we estimated the population exposed to transportation noise levels and determined how many people are vulnerable to noise levels that would cause serious annoyance and sleep disturbance. Compared with the World Health Organization [WHO] recommended levels, the daytime and nighttime transportation noise levels were still high enough to have the two psychosocial effects on people when considering the recommended levels of the World Health Organization (WHO; 55 decibels [dB[A]] and 40 dB[A] for daytime and nighttime, respectively). Particularly, nighttime transportation noise was discovered to be harmful to a wider area and more people than daytime noise. Approximately 91% of the Youngdeungpo-gu area experienced nighttime transportation noise levels exceeding those recommended by WHO. It was estimated that as much as 80% of the people in the study area were exposed to transportation noise levels >40 dB[A] during nighttime. Taking this into account, there is an urgent need to control and reduce transportation noise levels in Seoul, to protect residents against the potential ill health effects caused by urban transportation.     

From dummies to animations: a review of computer-animated stimuli used in animal behavior studies

Traditionally, studies that explored animal communication have been directed towards the observation of natural interactions between individuals. Over the years, researchers have long championed the use of artificial stimuli in place of natural ones in behavioral experiments to precisely control what the observers get to see or experience. The employment of diverse techniques to stage animal interactions has provided an alternative to observations and intrusive experimental methods. Technological advances now allow researchers to develop realistic computer animations of social partners that mimic behaviors with a high degree of fidelity for morphological and behavioral characteristics of tutors. The increasing use of the computer-generated animations technique reveals a desire to deliver standardized visual stimuli and to limit the variable behavior of demonstrators across experimental sessions. In the following review, we provide an appraisal of the computer-generated animations efficiency to stage animal interactions, and consider experimental studies in which this technique has been employed to simulate social interactions. We also present alternative methods that are used for designing animation models. Our aim is to evaluate the merits of computer-generated animations and how this technique may be more appropriate for certain types of staged interactions when compared to other classically employed approaches. We advocate that computer-generated animations appear to be the most flexible technique to date, and offers better control of visual cues that are presented, thus allowing researchers to program a large variety of stimuli. Finally, we suggest improvements of this technique, and especially how it may be used to study signal design in multimodal systems.     

Potential Impacts of Climate Change on the Reliability of Water and Hydropower Supply from a Multipurpose Dam in South Korea

Future climate change is a source of growing concerns for the supply of energy and resources, and it may have significant impacts on industry and the economy. Major effects are likely to arise from changes to the freshwater resources system, due to the connection of energy generation to these water systems. Using future climate data downscaled by a stochastic weather generator, this study investigates the potential impacts of climate change on long‐term reservoir operations at the Chungju multipurpose dam in South Korea, specifically considering the reliability of the supply of water and hydropower. A reservoir model, Hydrologic Engineering Center‐Reservoir System Simulation (HEC‐ResSim), was used to simulate the ability of the dam to supply water and hydropower under different conditions. The hydrologic model Soil and Water Assessment Tool was used to determine the HEC‐ResSim boundary conditions, including daily dam inflow from the 6,642 km² watershed into the 2.75 Gm³ capacity reservoir. Projections of the future climate indicate that temperature and precipitation during 2070‐2099 (2080s) show an increase of +4.1°C and 19.4%, respectively, based on the baseline (1990‐2009). The results from the models suggest that, in the 2080s, the average annual water supply and hydropower production would change by +19.8 to +56.5% and by +33.9 to 92.3%, respectively. Model simulations suggest that under the new climatic conditions, the reliability of water and hydropower supply would be generally improved, as a consequence of increased dam inflow.