Decision Tree-Based Classifier Combined with Neural-Based Predictor for Water-Stage Forecasts in a River Basin During Typhoons: A Case Study in Taiwan

To solve the complicated problem of water-stage predictions under the interaction of upstream flows and tidal effects during typhoon attacks, this article presents a novel approach to river-stage predictions. The proposed CART-ANN model combines both the decision trees (classification and regression trees [CART]) and the artificial neural network (ANN) techniques, which comprise the multilayer perceptron (MLP) and radial basis function (RBFNN). The combined CART-ANN model involves a two-step predicting process. First, the CART stage-level classifier can classify the river stages into higher, middle, and lower levels. Then, the ANN-based water-stage predictors are employed to predict the water stages. The proposed model was applied to the Tanshui River Basin in Taiwan. The Taipei Bridge, which is close to the estuary and affected by tidal effects, was taken as the study gauge. The mean square error and the mean absolute error were used for evaluating the variance and bias performances of the models. This study makes two contributions. First, the CART-MLP and CART-RBF were modeled to predict river stages under tidal effects during typhoons, and they were compared with three benchmark models, CART, back-propagation neural network, and RBFNN. Second, the CART-RBF successfully demonstrated that it achieved more accurate prediction than CART-MLP and three benchmark models.     

Dredged Material Disposal at the Edge of the Florida Current

A field data collection project was undertaken to investigate the short-term fate of dredged material discharged in the designated Miami Ocean Dredged Material Disposal Site (ODMDS) before dredging of the Miami River and the Miami Harbor Turning Basin begins. the designated ODMDS is located in relatively deep water for discharge sites with a typical bottom depth of 150 metres and is also located in the western boundary region of the Gulf Stream current off Miami. Acoustical backscattering, current, particulate, temperature and salinity data were gathered over a three day period from April 24, 1990 through April 26, 1990. the major generic features of shallow-water discharge plumes were observed to be present: (a) the presence of a rapid convective descending plume portion; (b) impact of that plume portion with the ocean bottom and concomitant generation of a bottom surge; (c) rapid horizontal width growth of the descending plume through entrainment; and (d) retention of a residual plume portion within the water column. A well-mixed upper water column layer extending to a depth of 40 to 60 metres below the surface of the ocean permitted measurements of the plume entrainment coefficient free from bottom boundary, water column density gradient, and vertical current shear effects which are usually present in relatively shallow, e.g. less than 40 metres bottom depth, coastal ocean discharge studies. Entrainment coefficient estimates obtained in this study were between 0.5 to 0.7. the residual water plume material was tracked over one-half hour during each of eight discharge events and was transported in a north-northeast direction.     

Acoustic Observations of Bottom Surge From Dredged Material Discharge in the Open Ocean

Bottom surges generated from dredged material discharges in the open ocean have been observed using high frequency acoustic concentration profilers in several field studies during the past five years. the locations, water depths, bottom slopes, oceanographic conditions, and dredged material composition differed from study to study. Observed surges at three dredged material disposal sites may develop more than one surge peak for a single discharge. for water depths of the order of 10 m, surge height of the leading peak was estimated to be about one quarter of the water depth. for water of greater depth, of the order of 100 m, surge height reached 70 m, about 70% of the water depth. Surge height is established instantaneously when dredged material hits the bottom, and remains relatively constant as the surge advances horizontally. Total surge length reached 150 m for water depths of 10 m when measured from the impact point to the leading edge. for water depths of more than 100 m, the surge length reached more than 100 m. Length of the leading surge peak was as large as 45 m at this water depth.

Dimensional analysis was applied to relate the surge height of the leading surge peak to discharge parameters and oceanographic conditions. Results showed that the ratio of surge height to water depth was proportional to 1/10 power of the ratio of discharge volume to the third power of water depth.     

Degradation of Polylactic Acid by Irradiation

Polylactic acid (PLA) waste has various treatment methods, such as natural decomposition, composting, incineration, and hydrolysis. Degradation of PLA waste by gamma ray and pulsed light irradiation is an efficient, safe and innovative method that also protects the environment. The focus of this study was on the development of an alternative, green technology for solving the PLA waste disposal problem of PLA, rather than using incineration or the landfill method. We used a novel approach to identify the thermal decomposition and heat properties of crystalline poly lactic acid, non-crystalline polylactic acid, and blend polylactic acid. The approach involved the degradation of the materials with gamma ray and pulsed light irradiation followed by thermogravimetric analysis (TGA). We also developed a novel approach to the heat effect, including heat reactivity properties by TGA tests and thermal mass loss simulation for proper application, processing, and waste treatment conditions. The data from this study can be used to improve the design of operation and waste treatment protocols for PLA, which will benefit the environment.     

Growth dynamics of major microbial populations during biodegradation of o-phthalate in anaerobic sediment slurries under a CO2/H2 atmosphere

o-Phthalate transformers increased about five orders of magnitude (to 1.6x10(11)cells g-1 sediment) just before the onset of fast biotransformation of o-phthalate (21.6 mg l-1) and then decreased sharply when the concentration of o-phthalate became low during biodegradation of o-phthalate in anaerobic sediment slurries under CO2/H2 (4:1, v/v). In contrast, the benzoate transformers increased about four orders of magnitude (to 1.6x10(11)cells g-1 sediment) in 48 days and then increased one more order (to 1.6x10(12)cells g-1 sediment) in 60 days and then remained at that high level in those sediment slurries. When making a comparison between the growth dynamics of o-phthalate transformers, acetogens, sulfate reducers, and methanogens and the time course of o-phthalate transformation, it appears that acetogens did not initiate biotransformation of o-phthalate, and that sulfate reducers and methanogens were not directly involved in o-phthalte degradation. o-Phthalate was not transformed in sediment slurries amended with BESA plus molybdate under CO2/H2.     

Ambient air particulates-bound metallic elements sources identifications during winter and summer at a Science Park

The ambient air particulates pollutants of total suspended particulates (TSP) and PM_2.5 were collected by using PS-1 and Wilbur PM_2.5 sampler, simultaneously during the year of 2015–2017 at a photoelectric factory in Science Park of central Taiwan. And those of the ambient air atmospheric metallic elements (Cr, Mn, Ni, Cu, Zn, Pb) concentrations which attached on the TSP and PM_2.5 were analyzed by using inductively coupled plasma optical emission spectrometer. In addition, identifying anthropogenic and natural pollutants sources were conducted by using the enrichment factor (EF) and principal component analysis (PCA) methods. The results indicated that the average TSP and PM_2.5 concentrations were ranked highest in winter season, while summer season was ranked lowest during the year of 2015–2016. In addition, the average highest metallic element concentrations were occurred in winter season for both TSP and PM_2.5 during the year of 2015–2016, while the average lowest metallic elements concentrations in TSP and PM_2.5 were also occurred in winter season during the year of 2016–2017. Moreover, the EF analysis results showed that the metallic element Zn came from anthropogenic emission source. As for metallic element Mn, the results showed that metallic element Mn was mainly attributed to natural emission in this study. Finally, the PCA results showed that metallic elements Cr, Zn and Pb were the dominant emissions metallic elements in this study. As for PM_2.5, the results showed that the metallic elements Cr, Cu and Pb were the dominant emissions metallic elements at this HPB sampling site.

     

Dynamical coupling of PBPK/PD and AUC-based toxicity models for arsenic in tilapia Oreochromis mossambicus from blackfoot disease area in Taiwan

A physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) models were developed for arsenic (As) in tilapia Oreochromis mossambicus from blackfoot disease area in Taiwan. The PBPK/PD model structure consisted of muscle, gill, gut wall, alimentary canal, and liver, which were interconnected by blood circulation. We integrate the target organ concentrations and dynamic response describing uptake, metabolism, and disposition of As and the associated area-under-curve (AUC)-based toxicological dynamics following an acute exposure. The model validations were compared against the field observations from real tilapia farms and previously published uptake/depuration experimental data, indicating that predicted and measured As concentrations in major organs of tilapia were in good agreement. The model was utilized to reasonably simulate and construct a dose-dependent dynamic response between mortality effect and equilibrium target organ concentrations. Model simulations suggest that tilapia gills may serve as a surrogate sensitive biomarker of short-term exposure to As. This integrated As PBPK/PD/AUC model quantitatively estimates target organ concentration and dynamic response in tilapia and is a strong framework for future waterborne metal model development and for refining a biologically-based risk assessment for exposure of aquatic species to waterborne metals under a variety of scenarios.