scholarly journals Measurement of Biochemical Methane Potential of Heterogeneous Solid Substrates: Results of a Two-Phase French Inter-Laboratory Study

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2814 ◽  
Author(s):  
Thierry Ribeiro ◽  
Romain Cresson ◽  
Sébastien Pommier ◽  
Sébastien Preys ◽  
Laura André ◽  
...  
Keyword(s):  
Biochemical Methane Potential ◽  
Two Phase ◽  
Bicarbonate Buffer ◽  
Solid Substrates ◽  
Methane Potential ◽  
Repeatability And Reproducibility ◽  
Substrate Ratio ◽  
Two Phases ◽  
Heterogeneous Solid ◽  
Previous Step

Biochemical methane potential (BMP) is essential to determine the production of methane for various substrates; literature shows important discrepancies for the same substrates. In this paper, a harmonized BMP protocol was developed and tested with two phases of BMP tests carried out by eleven French laboratories. Surprisingly, for the three same solid tested substrates (straw; raw mix and dried-shredded mix of potatoes, maize, beef meat and straw; and mayonnaise), the standard deviations of the repeatability and reproducibility inter-laboratory were not enhanced by the harmonized protocol (average of about 25% depending on the substrate), as compared to a previous step where all laboratories used their own protocols. Moreover, statistical analyses of all the results, after removal of the outliers (about 15% of all observations), did not highlight significant effect of the operational effect on BMP (stirring, automatic or manual gas quantification, use of trace metal, uses a bicarbonate buffer, inoculum to substrate ratio) at least for the tested ranges. On the other hand, the average intra-laboratory repeatability was low, about 7%, whatever the protocol, the substrate and the laboratory. It also appears that drying the SA substrate, which contained proteins, carbohydrates, lipids and fibers, does not impact its BMP.

scholarly journals Effect of the inoculum/substrate ratio on the biochemical methane potential (BMP) of grape marc

2020 ◽  
Vol 15 (5) ◽  
pp. 1
Author(s):  
Kessia Caroline Dantas da Silva ◽  
Miriam Cleide Cavalcante de Amorim ◽  
Renan Santana Galvão ◽  
Yandra Beatriz de Oliveira Gonçalves ◽  
Paula Tereza de Souza e Silva ◽  
...  
Keyword(s):  
Anaerobic Digestion ◽  
Biological Treatment ◽  
Organic Waste ◽  
Biochemical Methane Potential ◽  
Biomass Waste ◽  
Grape Marc ◽  
Nutritive Solution ◽  
Methane Potential ◽  
Industrialization Process ◽  
Substrate Ratio

The grape industrialization process produces large volumes of solid organic waste, with the grape bagasse being the main waste generated in the winemaking process. Anaerobic digestion can be used to treat and dispose of agro-industrial biomass waste. The objective of this study was to evaluate the effect of the inoculum/substrate ratio on the Biochemical Methane Potential (BMP) of grape marc. The experiment was performed in laboratory scale through a system of reactor bottles in batches, removing a set of triplicate flasks for sampling and analysis every 48 hours, with the test lasting 12 days. The reactors contained residue, inoculum and 20% of nutritive solution, maintaining 20% of headspace. The reactors were incubated in an incubator at a mesophilic temperature (35 ± 2°C) and shaken manually every 24 hours. Three different inoculum/substrate (I/S) ratios of 0.75, 1.5 and 3 were used to evaluate the methane yield, organic removals and at the end of degradation the morphology of the bacterial community was evaluated by means of scanning electron microscopy. The I/S 3 ratio provided the best results for loading anaerobic systems, indicating that grape marc presents potential for biological treatment through anaerobic digestion.

Effect of inoculum-substrate ratio on the start-up of solid waste anaerobic digesters

2001 ◽  
Vol 44 (4) ◽  
pp. 103-108 ◽  
Author(s):  
B. Fernández ◽  
P. Porrier ◽  
R. Chamy
Keyword(s):  
Solid Waste ◽  
Methane Production ◽  
Waste Treatment ◽  
Two Phase ◽  
Anaerobic Reactors ◽  
Start Up ◽  
Anaerobic Degradability ◽  
Substrate Ratio ◽  
Two Phases ◽  
Anaerobic System

The anaerobic systems start-up for solid waste treatment is a fundamental step, especially for those with two phases. It is necessary to know both the waste characteristics and the inoculum conditions. The objective of this work was to study the inoculum-substrate ratio (ISR) influence as a previous step of the start-up of an anaerobic system for the solid waste digestion. During this research spent grain was chosen as residue, working at three different concentrations (7; 13 and 20% w/v), studying the ISR effect in terms of anaerobic degradability (AD) and specific methane productivity (SMP). The initial acetoclastic activities (A0) were calculated based on the equation which describes the methane accumulation during each test. The model constants were also calculated and were adjusted to the experimental data. The results showed that in general the ISR variation has less impact on AD than on SMP. While maximum AD were reached in those tests with high ISR, the greatest values of SMP were with the lowest values of ISR ratio. A low ISR caused a slow hydrolysis, although the methane production was fast. So, during the start-up of a two-phase anaerobic system an elevated ISR would not be necessary in order to reach a good AD and a good intermediate products production, because the hydrolysis and the VFA production must be optimised in the first phase of these systems. While in conventional systems, where phases are together, it is much better to optimise the methane production. The ISR and the SMP indicated which inoculum percentage would be interesting based on the objective of the whole system: methane or intermediate compounds (VFA) production. All this information is important during the conventional anaerobic reactors operation because these tests would show which ISRs avoid inhibition.

Relationship of Substrate and Inoculum on Biochemical Methane Potential for Grass and Pig Manure Co-Digestion

2012 ◽  
Vol 512-515 ◽  
pp. 444-448 ◽  
Author(s):  
Sumeth Dechrugsa ◽  
Sumate Chaiprapat
Keyword(s):  
Methane Production ◽  
Methane Yield ◽  
Pig Manure ◽  
Biochemical Methane Potential ◽  
Production Potential ◽  
Methane Potential ◽  
Methane Production Rate ◽  
Substrate Ratio ◽  
Relationship Of ◽  
Careful Investigation

The effects of substrate mix ratio and inoculum/substrate ratio (ISR) on biochemical methane potential of para-grass (PG) and pig manure (PM) were investigated in batch test that maintained temperature at 35±1 oC and continuously shaked at 120 rpm. Cumulative methane production data at different mix ratios and ISRs were evaluated and fitted with Gompertz equation to derive methane production potential (mL) and maximum methane production rate (mL/d). The maximum and average methane yields at each respective ISR of 1, 2, 3, and 4 were [413.0, 315.5], [539.7, 455.6], [590.3, 472.5], and [593.1, 473.5] mL/gVSadded. Relationship of ISR and PG mix ratio to specific methane yield were expressed in quadratic regression model. The generated response surface showed that methane yield was elevated at higher ISR and higher PG mix ratio. This suggests a careful investigation at different ISR and substrate mix ratios should be performed in order to develop a realistic biochemical methane potential of anaerobic co-digestion.

Influence of inoculum to substrate ratio on the biochemical methane potential of maize in batch tests

2006 ◽  
Vol 41 (6) ◽  
pp. 1444-1450 ◽  
Author(s):  
F. Raposo ◽  
C.J. Banks ◽  
I. Siegert ◽  
S. Heaven ◽  
R. Borja
Keyword(s):  
Biochemical Methane Potential ◽  
Batch Tests ◽  
Methane Potential ◽  
Substrate Ratio

INFLUENCE OF FREEZING/THAWING AND DRYING/MILLING ON BIOCHEMICAL METHANE POTENTIAL

2016 ◽  
Vol 15 (7) ◽  
pp. 1533-1536
Author(s):  
Jin Mi Triolo ◽  
Sven Gjedde Sommer ◽  
Lene Pedersen
Keyword(s):  
Biochemical Methane Potential ◽  
Methane Potential

A Lightweight Formalism for Reference Lifetimes and Borrowing in Rust

2021 ◽  
Vol 43 (1) ◽  
pp. 1-73
Author(s):  
David J. Pearce
Keyword(s):  
Memory Management ◽  
Programming Model ◽  
Type System ◽  
Control Flow ◽  
Two Phase ◽  
Type Checking ◽  
Strong Focus ◽  
Reference Implementation ◽  
Two Phases ◽  
Complex Features

Rust is a relatively new programming language that has gained significant traction since its v1.0 release in 2015. Rust aims to be a systems language that competes with C/C++. A claimed advantage of Rust is a strong focus on memory safety without garbage collection. This is primarily achieved through two concepts, namely, reference lifetimes and borrowing . Both of these are well-known ideas stemming from the literature on region-based memory management and linearity / uniqueness . Rust brings both of these ideas together to form a coherent programming model. Furthermore, Rust has a strong focus on stack-allocated data and, like C/C++ but unlike Java, permits references to local variables. Type checking in Rust can be viewed as a two-phase process: First, a traditional type checker operates in a flow-insensitive fashion; second, a borrow checker enforces an ownership invariant using a flow-sensitive analysis. In this article, we present a lightweight formalism that captures these two phases using a flow-sensitive type system that enforces “ type and borrow safety .” In particular, programs that are type and borrow safe will not attempt to dereference dangling pointers. Our calculus core captures many aspects of Rust, including copy- and move-semantics, mutable borrowing, reborrowing, partial moves, and lifetimes. In particular, it remains sufficiently lightweight to be easily digested and understood and, we argue, still captures the salient aspects of reference lifetimes and borrowing. Furthermore, extensions to the core can easily add more complex features (e.g., control-flow, tuples, method invocation). We provide a soundness proof to verify our key claims of the calculus. We also provide a reference implementation in Java with which we have model checked our calculus using over 500B input programs. We have also fuzz tested the Rust compiler using our calculus against 2B programs and, to date, found one confirmed compiler bug and several other possible issues.

scholarly journals XCOVNet: Chest X-ray Image Classification for COVID-19 Early Detection Using Convolutional Neural Networks

2021 ◽  
Author(s):  
Vishu Madaan ◽  
Aditya Roy ◽  
Charu Gupta ◽  
Prateek Agrawal ◽  
Anand Sharma ◽  
...  
Keyword(s):  
Image Classification ◽  
Second Phase ◽  
Two Phase ◽  
X Ray ◽  
The Neural Network ◽  
Rapid Spread ◽  
Chest X Ray ◽  
Polymerase Chain ◽  
Two Phases ◽  
Active Patients

AbstractCOVID-19 (also known as SARS-COV-2) pandemic has spread in the entire world. It is a contagious disease that easily spreads from one person in direct contact to another, classified by experts in five categories: asymptomatic, mild, moderate, severe, and critical. Already more than 66 million people got infected worldwide with more than 22 million active patients as of 5 December 2020 and the rate is accelerating. More than 1.5 million patients (approximately 2.5% of total reported cases) across the world lost their life. In many places, the COVID-19 detection takes place through reverse transcription polymerase chain reaction (RT-PCR) tests which may take longer than 48 h. This is one major reason of its severity and rapid spread. We propose in this paper a two-phase X-ray image classification called XCOVNet for early COVID-19 detection using convolutional neural Networks model. XCOVNet detects COVID-19 infections in chest X-ray patient images in two phases. The first phase pre-processes a dataset of 392 chest X-ray images of which half are COVID-19 positive and half are negative. The second phase trains and tunes the neural network model to achieve a 98.44% accuracy in patient classification.

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