Tsunami mitigation by coastal vegetation considering the effect of tree breaking

Damage to vegetation by tsunami moment and reduction of potential tsunami force are discussed based on a numerical simulation. A numerical model based on two-dimensional nonlinear long-wave equations that include drag forces and turbulence-induced shear force due to the presence of vegetation was developed to estimate tree breaking. The numerical model was then applied to a coastal forest where two dominant tropical vegetation species, Pandanus odoratissimus and Casuarina equisetifolia, were considered. The threshold water depth for tree breaking increased with increasing forest width, and the analysis was consistent with the field investigation results that the critical tsunami water depth for breaking is around 80% of the tree height for P. odoratissimus. C. equisetifolia is stronger than P. odoratissimus against tsunami action, but P. odoratissimus can reduce a greater tsunami force than C. equisetifolia due to its complex of aerial root structures. Even if breakage occurs, P. odoratissimus still has high potential to reduce the tsunami force due to its dense aerial root structures. Previous numerical models that do not include the breaking phenomena may overestimate the vegetation effect for reducing tsunami force. The combination of P. odoratissimus and C. equisetifolia is recommended as a vegetation bioshield to protect coastal areas from tsunami hazards.     

Application of GIS and modelling in health risk assessment for urban road mobility

Transport is an essential sector in modern societies. It connects economic sectors and industries. Next to its contribution to economic development and social interconnection, it also causes adverse impacts on the environment and results in health hazards. Transport is a major source of ground air pollution, especially in urban areas, and therefore contributes to the health problems, such as cardiovascular and respiratory diseases, cancer and physical injuries. This paper presents the results of a health risk assessment that quantifies the mortality and the diseases associated with particulate matter pollution resulting from urban road transport in Haiphong City, Vietnam. The focus is on the integration of modelling and geographic information system approaches in the exposure analysis to increase the accuracy of the assessment and to produce timely and consistent assessment results. The modelling was done to estimate traffic conditions and concentrations of particulate matters based on geo-referenced data. The study shows that health burdens due to particulate matter in Haiphong include 1,200 extra deaths for the situation in 2007. This figure can double by 2020 as the result of the fast economic development the city pursues. In addition, 51,000 extra hospital admissions and more than 850,000 restricted activity days are expected by 2020.     

Accuracy improvement of various short-term load forecasting models by a novel and unified statistical data-filtering method

ABSTRACT

Time-series and machine-learning methods are being strongly exploited to improve the accuracy of short-term load forecasting (STLF) results. In developing countries, power consumption behaviors could be suddenly changed by different customers, e.g. industrial customers, residential customers, so the load-demand dataset is often unstable. Therefore, reliability assessment of the load-demand dataset is obviously necessary for STLF models. Hence, this paper proposes a novel and unified statistical data-filtering method with the best confidence interval to eliminate unexpected noises/outliers of the input dataset before performing various short-term load forecasting models. This proposed novel data-filtering method, so-called the data pre-processing method, is also compared to other existing data-filtering methods (e.g. Kalman filter, Density-Based Spatial Clustering of Applications with Noise, Wavelet transform, and Singular Spectrum Analysis). By using an SCADA system?-based database of a typical 22kV distribution network in Vietnam, NYISO database, and PJM-RTO database, case studies of short-term load forecasting have been conducted with a conventional ARIMA model, an ANN forecasting model, an LSTM-RNN model, an LSTM-CNN combined model, a deep auto-encoder (DAE) network, a Wavenet-based model, a Wavenet and LSTM hybrid model, and a Wavelet Neural Network (WNN) model, which are to validate the novel and unified statistical data-filtering method proposed. The achieved numerical results demonstrate which the accuracy of the aforementioned STLF models can be significantly improved due to the proposed statistical data-filtering method with the best confidence interval of the input load dataset. The proposed statistical data-filtering method can considerably outperform the existing data-filtering methods.     

Vision-independent odometry in the ant Cataglyphis cursor

In contrast to flying insects, in which distance estimation is visually mediated, self-induced image motion and use of familiar landmarks are known to play a minor role in ants. Here we show that strictly diurnal Cataglyphis cursor ants can gauge with accuracy the distance they have travelled even in complete darkness in the absence of any other cues, i.e. chemical or protocounting information. Thus, an ants odometer is a vision-independent system based on proprioceptive cues, implicating some form of step counting, which remain to be elucidated.     

Spring abundance and distribution of the ctenophore Pleurobrachia pileus in the Seine estuary: advective transport and diel vertical migration

Several sets of plankton and hyperbenthos samples were collected from the Seine estuary in late May-early June of 1991, 1992 and 1994, and the abundance, size-frequency, horizontal and vertical distribution, and short-term fluctuations of Pleurobrachia pileus (O.F. Müller, 1776) were determined. In the Seine estuary, P. pileus was more abundant than reported for any other European shallow waters. Its depth-averaged density was 33 individuals m^-3 in 1991 and 32 individuals m^-3 in 1992, with a maximum density of 808 individuals m^-3. The ctenophores displayed passive tidal advection and active diel vertical migration. In the outer estuary, high abundances were observed around low tide, and diel vertical migration was very pronounced. However, many individuals remained aggregated near the bottom at all times. In spring, the distribution of P. pileus coincided with the 33 and 150 S isohalines, with high abundances on the marine side of the estuary. It is suggested that aggregation of ctenophores near the bottom and diel vertical migration play an important role in the retention of P. pileus in the estuary. Two schemes of P. pileus life cycle in the Bay of Seine are proposed.     

Extraction,chemical compositions,and cytotoxic activities of essential oils of Thevetia peruviana

Abstract

In this study, The essential oil of flowers, fruits, and leaves of Thevetia peruviana, which were collected in Vietnam, were being reported for the first time. The essential oil of flowers was extracted by different methods: n-hexane extraction, distillation water, and supercritical CO₂ extraction. The compositions of essential oil of different parts of Thevetia peruviana were analyzed by GC-FID and GC/MS systems. Major chemical compositions of essential oil were identified as monoterpenes, sesquiterpenes, terpenoids, and sterol. The activities of total essential oil extracts of the Thevetia peruviana exhibit inhibitory activities against five cancer cell lines.     

An intergrated waste survey and environmental effects of COGIDO, a bleached pulp and paper mill in Vietnam, on the receiving waterbody

An integrated investigation on wastewater characterization and the environmental effects from the COGIDO pulp and paper mill in Bien Hoa Industrial Estate, Vietnam, a chlorine bleached soda integrated pulp and paper mill operating without a chemical recovery system, on the receiving water body was conducted during the rainy and dry seasons in 1993 and 1995. The pollution load from the mill was very high in terms of BOD, COD and SS (COD_m: 58.7 t/d; BOD: 33.3 t/d and SS: 25.1 t/d). The effluent toxicity was determined using four toxicity tests: the green micro-alga, Selenastrum capricornutum, Microtox (marine bacteria: Photobacterium phosphoreum), the duckweed, Lemna aequinoctialis, and fish (silver barb: Puntius gonionotus, and Tilapia: Tilapia nilotica). Selenastrum capricornutum was the most sensitive among the tested organisms. The mill toxicity emission rate (TER) was as high as 338 610 (Selenastrum test). The bleaching-pulp and semi-chemical pulp plants which contributed the largest pollution load to the total COGIDO effluent, therefore, were targeted for abatement measures. Physico-chemical parameters as well as qualitative and quantitative aquatic organism composition for the river water were established. The BOD₅ and COD values exceeded the potable surface water standard by a factor of 2 to 4. The species diversity and abundance of the phytoplankton, zooplankton and zoobenthos were found to be lower (20–40%) than that of unpolluted rivers in Vietnam, whereas pollution-indicator species increased up to four times during the dry season 1995.     

Influencing factors on sustainable development: a case study in Quang Tri province,Vietnam

Background Sustainable development (SD) is a common concept. Knowledge and attitudes are essential in the SD process. This study assesses the knowledge, attitudes, and practices (KAP) of local people about SD. Aim To study the factors that influence the understanding of the concept, contents, and indicators of different aspects affecting the health and environmental issues. Methods A cross-sectional study was carried out from June to July 2007 among 546 households in the Quang Tri province. Data were gathered on basis of socio-demographic variables, namely age, gender, education, occupation, income, and region. Chi square tests and multivariate analysis were performed on the obtained data. The data were cleaned and analysed using SPSS 15.0 for windows. Results Occupation is related to knowledge, attitude, or practice. Income is related to knowledge or practice. Gender related to only attitude. Lastly, region is related to attitude or practice. The proportion of wrong understanding about SD is 2.0 times (95% CI: 1.3; 3.1, p < 0.001) higher than that of the people who have good understanding about it. The rate of willingness to do any related SD programmes of the people who understanding is 2.1 times (95% CI: 1.4; 3.2, p < 0.001) higher than that of the people who have bad one. Conclusions This study shows that knowledge on sustainability of the local communities is low. Occupation and income influence understanding of SD more than region, age, gender, and education. Most of the local people who do not understand SD in general, do not want to participate or act in SD programmes.