The Kinetic Model of the Uptake and Release of Pollutants by Tubificidae in Sludge Reduction System

2014 ◽  
Vol 1010-1012 ◽  
pp. 551-559
Author(s):  
Ju Qing Lou ◽  
Dong Ye Yang ◽  
Ping Zheng ◽  
Mao Xin Guo ◽  
Pei De Sun
Keyword(s):  
Kinetic Model ◽  
Rate Constant ◽  
Ammonia Nitrogen ◽  
Sludge Reduction ◽  
Release Rates ◽  
Nonlinear Fitting ◽  
Reduction System ◽  
Fitting Method ◽  
Uptake Rate Constant ◽  
Uptake And Release

Tubificidae is often used in the wastewater treatment systems to minimize the sludge production. A two-compartment kinetic model was applied to simulate the uptake and release of C, N and P-bearing pollutants by Tubificidae in a sludge reduction system. The nonlinear fitting method was used to calculate the uptake rate constantK1and the release rate constantK2for TOC, TN and TP, which were 4.983, 25.764, 10.154 and 3.671, 23.683, 9.023, respectively. The model fitted quite well with the collected data, suggesting that the model was applicable. The results showed that Tubificidae activity would increase the C, N and P concentrations in the system, and the specific release rates of C, N and P-bearing pollutants were 4.31 mg COD/gL. hoffmeisteri· d, 0.722 mg TN/gL. hoffmeisteri· d, and 0.14 mg TP/gL. hoffmeisteri· d,respectively. Ammonia nitrogen contributed up to 70.42% of the released nitrogen.

scholarly journals A Novel Stoichio-Kinetic Model for the DPPH• Assay: The Importance of the Side Reaction and Application to Complex Mixtures

Antioxidants ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1019
Author(s):  
Lucrezia Angeli ◽  
Sebastian Imperiale ◽  
Yubin Ding ◽  
Matteo Scampicchio ◽  
Ksenia Morozova
Keyword(s):  
Antioxidant Activity ◽  
Kinetic Model ◽  
Rate Constant ◽  
High Resolution Mass Spectrometry ◽  
Sinapic Acid ◽  
Side Reaction ◽  
Main Reaction ◽  
Dpph Assay ◽  
Best Fitting ◽  
The Common

The 2,2-diphenyl-1-picrylhydrazyl (DPPH•) assay is widely used to determine the antioxidant activity of food products and extracts. However, the common DPPH• protocol uses a two-point measurement and does not give information about the kinetics of the reaction. A novel stoichio-kinetic model applied in this study monitors the consumption of DPPH• by common antioxidants following the second order reaction. The fitting of such decay yields the rate constant k1, which describes the main reaction between antioxidants and DPPH•, and the rate constant k2, which is attributed to a slower side reaction considering the products generated between the transient radicals (AO•) and another molecule of DPPH•. The model was first applied to antioxidant standards. Sinapic acid, Trolox and ascorbic and chlorogenic acids did not show any side reaction. Instead gallic, ferulic and caffeic acids achieved the best fitting with k2. The products of the side reaction for these compounds were confirmed and identified with high-resolution mass spectrometry. Finally, the kinetic model was applied to evaluate the antioxidant activity of eight herbal extracts. This study suggests a new kinetic approach to standardize the common DPPH• assay for the determination of antioxidant activity.

scholarly journals Central Composite Design, Kinetic Model, Thermodynamics, and Chemical Composition of Pomelo (Citrus Maxima (Burm.) Merr.) Essential Oil Extraction by Steam Distillation

Processes ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 2075
Author(s):  
Tan Phat Dao ◽  
Thanh Viet Nguyen ◽  
Thi Yen Nhi Tran ◽  
Xuan Tien Le ◽  
Ton Nu Thuy An ◽  
...  
Keyword(s):  
Activation Energy ◽  
Kinetic Model ◽  
Essential Oil ◽  
Rate Constant ◽  
Flow Rate ◽  
Steam Distillation ◽  
Extraction Process ◽  
Oil Extraction ◽  
Extraction Time ◽  
Pomelo Peel

Pomelo peel-derived essential oils have been gaining popularity due to greater demand for stress relief therapy or hair care therapy. In this study, we first performed optimization of parameters in the pomelo essential oil extraction process on a pilot scale to gain better insights for application in larger scale production. Then extraction kinetics, activation energy, thermodynamics, and essential oil quality during the extraction process were investigated during the steam distillation process. Three experimental conditions including material mass, steam flow rate, and extraction time were taken into consideration in response surface methodology (RSM) optimization. The optimal conditions were found as follows: sample weight of 422 g for one distillation batch, steam flow rate of 2.16 mL/min and extraction time of 106 min with the coefficient of determination R2 of 0.9812. The nonlinear kinetics demonstrated the compatibility of the kinetic model with simultaneous washing and unhindered diffusion with a washing rate constant of 0.1515 min−1 and a diffusion rate constant of 0.0236 min−1. The activation energy of the washing and diffusion process was 167.43 kJ.mol−1 and 96.25 kJ.mol−1, respectively. The thermodynamic value obtained at the ΔG° value was −35.02 kJ.mol−1. The quality of pomelo peel essential oil obtained by steam distillation was characterized by its high limonene content (96.996%), determined by GC-MS.

Connecting charge transfer kinetics to device parameters of a narrow-bandgap polymer-based solar cell

2016 ◽  
Vol 18 (38) ◽  
pp. 26550-26561 ◽  
Author(s):  
Jongwoo Song ◽  
Younah Lee ◽  
Boa Jin ◽  
Jongdeok An ◽  
Hyunmin Park ◽  
...  
Keyword(s):  
Charge Transfer ◽  
Solar Cell ◽  
Kinetic Model ◽  
Rate Constant ◽  
Transfer Rate ◽  
Polymer Solar Cell ◽  
Transfer Rate Constant ◽  
Charge Transfer Rate ◽  
Narrow Bandgap

The spectroscopic charge transfer rate constant was compared with the PV properties of a polymer solar cell using a kinetic model.

scholarly journals A Novel Adaptive Non-Local Means-Based Nonlinear Fitting for Visibility Improving

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 741
Author(s):  
Hongtao Wu ◽  
Lei Jia ◽  
Ying Meng ◽  
Xiao Liu ◽  
Jinhui Lan
Keyword(s):  
Filter Design ◽  
Trade Off ◽  
Nonlinear Fitting ◽  
Local Means ◽  
Fitting Method ◽  
Central Pixel ◽  
Smooth Plane ◽  
Non Local ◽  
Geometric Surface ◽  
Weight Coefficients

The spatial-based method has become the most widely used method in improving the visibility of images. The visibility improving is mainly to remove the noise in the image, in order to trade off denoising and detail maintaining. A novel adaptive non-local means-based nonlinear fitting method is proposed in this paper. Firstly, according to the smoothness of the intensity around the central pixel, eight kinds of templates with different precision are exploited to approximate the central pixel through a novel adaptive non-local means filter design; the approximate weight coefficients of templates are derived from the approximation credibility. Subsequently, the fractal correction is used to smooth the denoising results. Eventually, the Rockafellar multiplier method is employed to generalize the smooth plane fitting to any geometric surface, thus yielding the optimal fitting of the center pixel approximation. Through a large number of experiments, it is clearly elucidated that compared with the classical spatial iteration-based methods and the recent denoising algorithms, the proposed algorithm is more robust and has better effect on denoising, while keeping more original details during denoising.

Predicting overall survival (OS) and overall response (OR) following durvalumab treatment in patients with multiple cancer types using a hybrid modeling strategy.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15161-e15161
Author(s):  
Ting Chen ◽  
Yanan Zheng ◽  
Lorin Roskos ◽  
Donald E Mager
Keyword(s):  
Kinetic Model ◽  
Kinetic Parameters ◽  
Rate Constant ◽  
Tumor Size ◽  
Hybrid Modeling ◽  
Tumor Growth Rate ◽  
Growth Rate Constant ◽  
Model Parameters ◽  
Cancer Types ◽  
Modeling Strategy

e15161 Background: This study aimed to predict OS/OR and identify key predictors in patients with diverse cancer types treated with durvalumab, a PD-L1 targeting monoclonal antibody, using a hybrid modeling strategy that combines population pharmacodynamic (PD) modeling and machine learning (ML) algorithms. Methods: Individual longitudinal tumor size measurements and OS/OR data were available for 855 patients who received durvalumab therapy (10 mg/kg Q2W or 20 mg/kg Q4W; NCT01693562). Nine cancer types included non-small cell lung cancer (NSCLC), bladder cancer (BC), microsatellite instability-high (MSI-H) cancer, hepatocellular carcinoma (HCC), squamous cell carcinoma of the head and neck (SCCHN), gastroesophageal cancer (GEC), ovarian cancer (OC), pancreatic adenocarcinoma (PDAC) and triple-negative breast cancer (TNBC). A tumor kinetic model was developed to characterize diverse temporal profiles using a population-based modeling approach. Individual estimated tumor kinetic model parameters and patient demographic/physiological factors were used as inputs for predicting OS/OR using several ML approaches. Results: The final tumor kinetic model with liver metastasis (LM), neutrophil/lymphocyte ratio (NLR), tumor size at baseline (TBSL) and cancer types as covariates characterized the temporal tumor size data well. HCC and MSI-H cancer have the slowest tumor growth rate constant (kg), while GEC, SCCHN and TNBC have the fastest kg. BC, NSCLC and OC have the highest tumor killing rate constant. The most important predictors of OS identified by ML approach were tumor kinetic parameters (kg, fraction of drug-sensitive cells, time-delay in immune response), along with baseline disease factors, including hemoglobin (HGBBL), albumin (ALB), and NLR. Decision tree-based algorithms showed the best performance in predicting OR with accuracy above 90%. In addition to tumor kinetic parameters, PD-L1 expression on tumor cells (TC) and ALB were the most important predictors of OR. Conclusions: A combined population PD/ML approach showed good predictions of OS/OR in patients with different cancer types treated with durvalumab. LM, NLR,TBSL and cancer types were found to be important factors for tumor kinetics. In addition to tumor kinetic parameters, HGBBL, ALB, and NLR were found to be important predictors of OS, and TC and ALB were found to be important predictors of OR. These findings could provide a guidance on patient selection in future clinical trials.

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