Short‐term effect of the inoculation of probiotics in mature bioflocs: Water quality parameters and abundance of heterotrophic and ammonia‐oxidizing bacteria

2019 ◽  
Vol 51 (1) ◽  
pp. 255-264 ◽  
Author(s):  
Anselmo Miranda‐Baeza ◽  
Mariela Nolasco‐López ◽  
Martha Elisa Rivas‐Vega ◽  
José Alberto Huerta‐Rábago ◽  
Luis Rafael Martínez‐Córdova ◽  
...  
Keyword(s):  
Water Quality ◽  
Quality Parameters ◽  
Term Effect ◽  
Water Quality Parameters ◽  
Ammonia Oxidizing Bacteria ◽  
Short Term ◽  
Short Term Effect

scholarly journals Implementation of Long-Short Term Memory Neural Network (LSTM) for Predicting The Water Quality Parameters in Sungai Selangor

2021 ◽  
Vol 6 (4) ◽  
pp. 40-49
Author(s):  
Nur Natasya Mohd Anuar ◽  
Nur Fatihah Fauzi ◽  
Huda Zuhrah Ab Halim ◽  
Nur Izzati Khairudin ◽  
Nurizatul Syarfinas Ahmad Bakhtiar ◽  
...  
Keyword(s):  
Water Quality ◽  
Short Term Memory ◽  
Oxygen Demand ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Short Term ◽  
Term Memory ◽  
Quality Of Water ◽  
Long Short Term Memory

Predictions of future events must be factored into decision-making. Predictions of water quality are critical to assist authorities in making operational, management, and strategic decisions to keep the quality of water supply monitored under specific criteria. Taking advantage of the good performance of long short-term memory (LSTM) deep neural networks in time-series prediction, the purpose of this paper is to develop and train a Long-Short Term Memory (LSTM) Neural Network to predict water quality parameters in the Selangor River. The primary goal of this study is to predict five (5) water quality parameters in the Selangor River, namely Biochemical Oxygen Demand (BOD), Ammonia Nitrogen (NH3-N), Chemical Oxygen Demand (COD), pH, and Dissolved Oxygen (DO), using secondary data from different monitoring stations along the river basin. The accuracy of this method was then measured using RMSE as the forecast measure. The results show that by using the Power of Hydrogen (pH), the dataset yielded the lowest RMSE value, with a minimum of 0.2106 at station 004 and a maximum of 1.2587 at station 001. The results of the study indicate that the predicted values of the model and the actual values were in good agreement and revealed the future developing trend of water quality parameters, showing the feasibility and effectiveness of using LSTM deep neural networks to predict the quality of water parameters.

scholarly journals R.A.OLAOYE et al. 2021 Variation of Groundwater and Rainwater Quality in a Nigerian Leper Colony

2021 ◽  
Vol 2 (3) ◽  
pp. 27-33
Author(s):  
Rebecca A. Olaoye ◽  
Akinwale O. Coker ◽  
Mynepalli K. Sridhar
Keyword(s):  
Water Quality ◽  
Water Samples ◽  
Quality Parameters ◽  
Water Sources ◽  
Water Quality Parameters ◽  
World Health ◽  
Slight Variation ◽  
Short Term ◽  
Adequate Treatment ◽  
Bacteriological Parameters

Adequate supply of potable water is a major challenge in most leper colony with emphasis often placed on water needs of “normal” people but little concern on the safe water source for the physically challenged and vulnerable lepers with limited mobility who cannot search for other sources of water outside designated colony. This study was designed to investigate the quality of water sources within a Nigerian leper colony. Periodic characterization of groundwater and rainwater samples was conducted using American Public Health Association (APHA) methods to determine physico-chemical parameters; appearance, odour, colour, taste, chloride, pH, sulphate, copper, zinc, iron, nitrate and bacteriological parameters; coliform organism and Escherichia coli (E-coli) against the world health organization (WHO) drinking water standard. Water samples were clear and odourless. Most of the parameters tested from both sources; groundwater and rainwater were within the recommended standard. Results from short term water quality parameters taken from 2010-2012 were relatively within the same range while the long-term decadal water quality parameters showed slight variation compared to the short term. Heavy metals showed remarkable variation in 2019 while bacteriological parameters from both water sources were above the permissible threshold. For potable use, water sources require adequate treatment. Boiling or disinfection is recommended until water samples have been retested to ascertain that contamination has been eliminated. In addition, home water-treatment through the use of filters, solar disinfection, or flocculants should be provided to make the water safe.

scholarly journals A Water Quality Prediction Method Based on the Deep LSTM Network Considering Correlation in Smart Mariculture

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1420 ◽  
Author(s):  
Zhuhua Hu ◽  
Yiran Zhang ◽  
Yaochi Zhao ◽  
Mingshan Xie ◽  
Jiezhuo Zhong ◽  
...  
Keyword(s):  
Water Quality ◽  
Water Temperature ◽  
Prediction Accuracy ◽  
Prediction Method ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Quality Prediction ◽  
Short Term ◽  
Water Quality Prediction ◽  
Term Prediction

An accurate prediction of cage-cultured water quality is a hot topic in smart mariculture. Since the mariculturing environment is always open to its surroundings, the changes in water quality parameters are normally nonlinear, dynamic, changeable, and complex. However, traditional forecasting methods have lots of problems, such as low accuracy, poor generalization, and high time complexity. In order to solve these shortcomings, a novel water quality prediction method based on the deep LSTM (long short-term memory) learning network is proposed to predict pH and water temperature. Firstly, linear interpolation, smoothing, and moving average filtering techniques are used to repair, correct, and de-noise water quality data, respectively. Secondly, Pearson’s correlation coefficient is used to obtain the correlation priors between pH, water temperature, and other water quality parameters. Finally, a water quality prediction model based on LSTM is constructed using the preprocessed data and its correlation information. Experimental results show that, in the short-term prediction, the prediction accuracy of pH and water temperature can reach 98.56% and 98.97%, and the time cost of the predictions is 0.273 s and 0.257 s, respectively. In the long-term prediction, the prediction accuracy of pH and water temperature can reach 95.76% and 96.88%, respectively.

scholarly journals Abundance and community structure of ammonia-oxidizing bacteria in activated sludge from different geographic regions in China

2018 ◽  
Vol 77 (6) ◽  
pp. 1698-1705 ◽  
Author(s):  
Rujia He ◽  
Dayong Zhao ◽  
Huimin Xu ◽  
Rui Huang
Keyword(s):  
Water Quality ◽  
Wastewater Treatment ◽  
Community Structure ◽  
Activated Sludge ◽  
Geographic Distribution ◽  
Quantitative Polymerase Chain Reaction ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Ammonia Oxidizing Bacteria ◽  
Ecological Information

Abstract Detailed ecological information on ammonia-oxidizing bacteria (AOB) in activated sludge of wastewater treatment plants (WWTPs) is very important to improve the efficiency of wastewater treatment. In this study, activated sludge samples were collected from seven municipal WWTPs located in seven cities in China, and real-time quantitative polymerase chain reaction (qPCR), as well as construction of clone libraries combined with correlation-based data analysis was performed. Further, the effect of geographic distribution and some water quality parameters on the ecological distribution of AOB in activated sludge from WWTPs were investigated. The geographic distribution, the influent concentration of total nitrogen (TN) and ammonia nitrogen (NH4+-N) had significant effects on the abundance of AOB (P < 0.05). However, the community structure of AOB were not significantly affected by geographic distribution, but by water quality parameters including the concentrations of TN and NH4+-N. N. oligotropha lineage was the dominant AOB group in the wastewater treatment systems. The results obtained in this study provide useful information to understand some aspects of the ecological information and influencing factors of AOB in geographically distributed WWTPs.

A Newspaper’s Effect on the Strength of Automatic Associations in Memory

2012 ◽  
Vol 24 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Florian Arendt
Keyword(s):  
Treatment Group ◽  
Term Effect ◽  
Control Group ◽  
Implicit Measure ◽  
Short Term ◽  
Short Term Treatment ◽  
Short Term Effect ◽  
Automatic Associations ◽  
Foreign Nationality ◽  
The Impact

A test was done to see if reading a newspaper which consistently overrepresents foreigners as criminals strengthens the automatic association between foreign country and criminal in memory (i.e., implicit cultivation). Further, an investigation was done to find out if reading articles from the same newspaper produces a short-term effect on the same measure and if (1) emotionalization of the newspaper texts, (2) emotional reactions of the reader (indicated by arousal), and (3) attributed text credibility moderate the short-term treatment effect. Eighty-five participants were assigned to one of three experimental conditions. Participants in the control group received short factual crime texts, where the nationality of the offender was not mentioned. Participants in the factual treatment group received the same texts, but the foreign nationality was mentioned. Participants in the emotionalized treatment group received emotionalized articles (i.e., texts which are high in vividness and frequency) covering the same crimes, with the foreign nationality mentioned. Supporting empirical evidence for implicit cultivation and a short-term effect was found. However, only emotionalized articles produced a short-term effect on the strength of the automatic association, indicating that newspaper texts must have a minimum of stimulus intensity to overcome an effect threshold. There were no moderating effects of arousal or credibility pertaining to the impact on the implicit measure. However, credibility moderated the short-term effect on a first-order judgment (i.e., estimated frequency of foreigners of all criminals). This indicates that a newspaper’s effect on the strength of automatic associations is relatively independent from processes of propositional reasoning.

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