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Phosphorus

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Contribution of phosphorus and PTH to the development of cardiac hypertrophy and fibrosis in an experimental model of chronic renal failure.

Nefrologia
BACKGROUND AND OBJECTIVE: Adequate serum phosphorus levels in patients with chronic kidney disease is essential for their clinical management. However, the control of hyperphosphatemia is difficult because is normally associated with increases in ser...

Combined effects of volume ratio and nitrate recycling ratio on nutrient removal, sludge characteristic and microbial evolution for DPR optimization.

Journal of environmental sciences (China)
The optimization of volume ratio (V/V/V) and nitrate recycling ratio (R) in a two-sludge denitrifying phosphorus removal (DPR) process of Anaerobic Anoxic Oxic-Moving Bed Biofilm Reactor (A/O-MBBR) was investigated. The results showed that prolonged ...

Effects of nitrogen and phosphorus addition on growth and leaf nitrogen metabolism of alfalfa in alkaline soil in Yinchuan Plain of Hetao Basin.

PeerJ
Alkaline soil is widely distributed in China. Its rational utilization is an effective measure to solve land shortage and improve the environment. Alfalfa is characterized by strong salt and alkali tolerance and high yield and protein content. Nitrog...

An influent responsive control strategy with machine learning: Q-learning based optimization method for a biological phosphorus removal system.

Chemosphere
Biological phosphorus removal (BPR) is an economical and sustainable processes for the removal of phosphorus (P) from wastewater, achieved by recirculating activated sludge through anaerobic and aerobic (An/Ae) processes. However, few studies have sy...

Comparing artificial intelligence techniques for chlorophyll-a prediction in US lakes.

Environmental science and pollution research international
Chlorophyll-a (CHLA) is a key indicator to represent eutrophication status in lakes. In this study, CHLA, total phosphorus (TP), total nitrogen (TN), turbidity (TB), and Secchi depth (SD) collected by the United States Environmental Protection Agency...

Application of artificial neural network and multiple linear regression in modeling nutrient recovery in vermicompost under different conditions.

Bioresource technology
Vermicomposting is one of the best technologies for nutrient recovery from solid waste. This study aims to assess the efficiency of Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) models in predicting nutrient recovery from solid...

Powerful, transferable representations for molecules through intelligent task selection in deep multitask networks.

Physical chemistry chemical physics : PCCP
Chemical representations derived from deep learning are emerging as a powerful tool in areas such as drug discovery and materials innovation. Currently, this methodology has three major limitations - the cost of representation generation, risk of inh...

Spectral Diagnostic Model for Agricultural Robot System Based on Binary Wavelet Algorithm.

Sensors (Basel, Switzerland)
The application of agricultural robots can liberate labor. The improvement of robot sensing systems is the premise of making it work. At present, more research is being conducted on weeding and harvesting systems of field robot, but less research is ...

In vivo magnetic resonance P-Spectral Analysis With Neural Networks: 31P-SPAWNN.

Magnetic resonance in medicine
PURPOSE: We have introduced an artificial intelligence framework, 31P-SPAWNN, in order to fully analyze phosphorus-31 ( P) magnetic resonance spectra. The flexibility and speed of the technique rival traditional least-square fitting methods, with th...

Large-scale prediction of stream water quality using an interpretable deep learning approach.

Journal of environmental management
Deep learning methods, which have strong capabilities for mapping highly nonlinear relationships with acceptable calculation speed, have been increasingly applied for water quality prediction in recent studies. However, it is argued that the practica...