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Decomposition - Science topic

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I am getting error when trying to react gypsum with biomass (ultimate) in a Gibbs reactor.
ERROR
RGIBBS DID NOT CONVERGE. MAXIMUM ITERATIONS EXCEEDED
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You could try just increasing number of iterations, if you haven't already, otherwise one workaround is to use an RStoich reactor and put the products into an RGibbs, which in principle should get to the same equilibrium.
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Hello, I have synthesized a powdery material that is highly sensitive to air and decomposes when exposed to air for a short period of time (a few seconds). Is there any way to prevent or delay sample decomposition for FTIR analysis? If I can't use this method to analyze my sample, what other method do you suggest?
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Thank you all for the guidance and putting me on the right way.
I wish you the bests.
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If input array is 2000*2000*3000 or larger, how can we decompose it with limited memory?
Most packages on tensor decomposition or factor analysis method, were not suitable to deal with large array.
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Hello Wang,
For some time, a number of software packages have been developed to handle data sets larger than what can reside in memory. This is typically accomplished by: (a) using updating algorithms for summary statistics and covariances/correlations; (b) writing intermediate results to disk; and/or (c) using disk storage as virtual memory (sometimes managed by the OS, sometimes by the software). The only downside of (c) is that it renders the process notably slower, though SSD drives will minimize the lag compared to traditional hard drives.
As an example, stata offers versions that can handle up to 120,000 variables and 20 billion cases, but require considerably less memory (e.g., 4 Gbytes) in order to function satisfactorily. (https://www.stata.com/products/).
Some of the R libraries have very large capacity, though if the largest object (for you, your data frame) exceeds about 35% of physical memory, virtual memory will likely be used during the processing).
One final point, for factor analysis, the data frame is two-dimensional: some objects to be factored and some replications dimension. So, I wasn't fully clear on the 3-D data set.
Good luck with your work.
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I have been reading “Handbook of reference methods for plant analysis” (Kalra (ed.), 1998) and other methodological books and papers to learn how to properly dry and analyse samples of vegetables and other sources of organic matter (manure, or compost).
On the drying procedure, it is cleat to me that:
i) Above 60ºC you stop the enzimatic activity and microbial decomposition and the sample is dry enough to be powdered and analysed (Carbon and nitrogen in a CNHS elemental analyzer, and P and K by digestions and mass spectophotometer), but it is not completely dried.
ii) From 80ºC the sample must reach a water content of 2-5%, and thermal decomposition starts, but it can be only problematic in powered samples.
iii) At 105ºC you have lost some elements by volatilization (N and S, and probably a little part of C), therefore it’s not recomended to dry at this temperature for elemental analysis. The sample is completely dried. There’s some thermal decomposition but nobody takes it into account.
In most works, if they want to know the nutrient contents and the dry matter content, they dry a subsample at 60º (and analyse its content in NPK) and other at 105º (and calculate the dry matter content).
My question is: how do you assign the nutrient content obtained with the sample at 60º to the dry matter, if you don’t know the water content of the sample dried at 60º? Should you take another subsample of the 60ºC subsample and dry it at 105º? Other researchers confirmed me that they dry all the samples at 105ºC, even for elemental analysis. How much nitrogen and carbon can we lose at 105ºC? I guess it depends on the element form (if N is in NH3, NO3-... ), but on average for plant tissue, manure, or compost, does anyone know how much it could be?
On the other hand, biomass is matter mainly composed of carbon and hidrogen, with small amounts of other elements. To measure the organic matter content of a sample, it is incinerated at 550º or more, and the difference in mass from the dried sample to the incinerated matter is assumed to be the organic matter.
The question is, why do atoms of P and other elements bonded to carbon structure are not considered as organic matter? Probably it is not easily measurable, but from the definition of organic matter, I understand that these elements are part of it. In addition, some elements like nitrogen or sulphur that don’t stay on the ashes are also considered organic matter (because they contribute to the mass loss when incinerated). I guess that these elements don’t represent too much, but I am surprised that nobody accounts them.
Thank you in advance.
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Air-dried/oven-dried at 105 to 110 °C or sun-dried.
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Hello everyone!
I have an ECG signal sampled at 500 Hz and, from that, I would like to compute the RR interval and then Welch's PSD. All this aims to understand the sympathetic activation of the person.
I wanted to enhance the R peaks using the 'sym4' wavelet. However, I have some difficulties in understanding how to choose the proper level of decomposition.
Can someone help me with this topic? Is there a "standard" way to assess the proper level of decomposition?
Thank you in advance for your time!
Luca
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There is an equation that can be used to determine the maximum level of decomposition.
Max Level = fix(length_of_the_signal/(length_of_the_filter-1))
Or you can simply use the inbuilt matlab function "wmaxlev(sizeX,wname)" to determine the level.
If you want to understand more about the working of the function you can always check the source code by typing the command "open('wmaxlev')"
Hope that works for you!
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Hello, I am a graduate student from Lanzhou University in China, and I am now very interested in the biochemical cycle in the context of global climate change, especially the decomposition of litter, but because I have just been exposed to this field, I am not very familiar with this field. My current idea is to link the decomposition process of litter under warming and rainfall changes with the aboveground plant community and the underground microbial decomposer community, but I don't know which scientific problem to start from, I hope you will provide me with some research ideas if you have time, thank you very much!
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Les champignons sont aussi très importants pour la décomposition de la matière ligneuse.
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Lower Matrix to represent the approximate final stages of payment and upper representing the early payments
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LU decomposition is a basic technique in numerical linear algebra. Numerical linear algebra has many applications, since a vast numerical algorithms reduce to linear algebra.
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Actually, I wish to understand the process and coding to define new wavelet transform. So that I can understand and modify some wavelet transform to get better results. There is inbuilt wavelet transform in MATLAB and we just have to choose wavelets. I wish to define new wavelet transform.
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By converting the signal from 2 dimensional signal to 1 dimensional, the transformation could be processed on vectors.
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The processes that soil microbes convert organic matter to carbon dioxide can be termed "decomposition" or "mineralization". The difference between these two words is still ambiguous to me.
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Mineralization , is the process by which an inorganic substance precipitates in an organic matrix , while Decomposition, is the process by which dead organic substances are broken down into simpler organic or inorganic matter
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Hello,
I'm looking for any additive to reduce the decomposition point of a dye. Any suggestions?
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I understand you want to increase thermal stability. I am an analytical chemist. It's not about my field. However, I can say this. No matter how many stages of degradation occur, each stage gives you a chance to intervene. The solvent affects the stability. The chromophores, double bonds, aromatic groups carried by the dye reduce the wavelength, and substitute groups such as tert-butyl sec-butly, isopropyl and methyl increase the thermal stability. Removing water from the environment can be beneficial when working with anhydrous dyes.
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We have known the distance matrix (n*n samples) and feature abudance (n samples*s features).
How can we extract featrue importance through matrix decomposition or something else?
Thank you for your help!
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Это можно сделать вычисляя удельный вес каждого фактора в итоговом разбросе, через дисперсионный или факторный анализ, также через расчет безусловной и условной энтропии.
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I am implementing Distributionally robust optimization using bender decomposition in GAMS. Can anyone provide me with any helping material or source code for the implementation of expansion planning problems?
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Hi community,
I have a question regarding the H-α, H-β and H-γ behavior in a CH4/N2 plasma.
Long story short: I am igniting a 5 sccm: 200 sccm CH4/N2 plasma (40W CCP plasma) at 5 mbar. Then I observe the plasma via a spectrometer. I did that for various temperatures inside my chamber.
Now I observe some typical Peaks. Most are related to N2 of course. And also the Balmer series.
What puzzles me is the transition from a increasing trend for the H-α and H-β lines but a decreasing trend for the H-γ line. Normaly I'd say these line can correspond to a) the density of hydrogen or b) to the mean energy of my electrons in the plasma. No hydrogen = no balmer series or no energy = no balmer series.
Clearly there is hydrogen. Most likely even more free hydrogen with icnreasing temperature. So why would the H-γ behave like it does? The energy difference between the three lines is not very big, so we should see a similar trend, right?
tl;dr: Do the three lines (H-α, H-β and H-γ) of the Balmer series have to follow the same intensity trend? Or can they show different behaviour? If so, why?
Thank you for your support :)
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Interesting thought. I can see how this could be potentially true for my plasma. Is there an easy way to measure the distribution of the electron temperatures?
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Is there any method that can assist me in estimating the decomposition rate of residues in the field?
For example, if we applied paddy residue at a rate of 6 t/ha, how can we estimate how much residue (t/ha) decomposed during the crop's growing cycle?
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You better calculate C:N ratio of initial sample and then final sample.
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I have just finished running a plant decomposition experiment measuring the decomposition of pine needles across climate and lithological types. We have mass loss and plant chemistry data (c, n, labile carbon, cellulose, hemicellulose and lignin). I would like to fit a three pooled decomposition model in r but am struggling to figure out how. I would usually do this in sigmaplot but my licence has expired and I cannot get another key.
Any help is greatly appreciated
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The 3-pool model can be fitted to experimental data using non-linear regression that minimizes the sum of simulation errors. Probably the simplest way is just the standard Solver in MS Excel. I am sure that non-linear regression solutions are available in other software packages like R, Python, Matlab, etc. Having said that, I confirm the opinion expressed by Andrew Paul McKenzie Pegman : the pooled decay model ignores interactions and generally true mechanisms of decomposition. It is not only an oversimplification of reality but rather a misconception, a wrong interpretation of the soil process. A discussion can be viewed in RG, see 'How fast can soil organic matter loss occur?'
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please I need suggestion and related materials from experts.
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Please refer to the following link.
Regards
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i need some helping material regarding hilbert transform and empirical mode decomposition. i want to apply on my vibration signal to evaluate the frequency at different phases of the signal. i am using EMD in matlab. if there is some kind of code regarding this kindly share. i want to ask some question related to EMD and hilbert transform
i will be thankful
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I tried EMD and its modifications. Also Hilbert transform and Teager kaiser Energy operator for the estimation of parameters. If you find any difficulties in these methods, please let me know, I can help.
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I need to decompose a signal on Matlab but I ended up having IMFs that with FFT instead of having one peak it shows several. Does anyone know how to decompose a signal with this method?
I'd be appreciated someone who could help me out
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I am using the code of TVf EMD, I got good results for the application in the power system. I am using spectral analysis too. If you have any doubts about this. Please let me know.
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In CP decomposition, how can we determine the component number for CP decomposition?
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Dear Wang,
In a tensor decomposition like PCA, the percent of explained variance can be calculated as the ratio of each eigenvalue to the sum of eigenvalues. The number of dimensions to reject should depend on the amount of variance to be maintained. In practice, this variance should never be less than 60%, although 80% or more is preferred. The lesser the explained variance, the lesser the confidence in the model.
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Need to know logic behind it
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Decomposition is a general approach to solving a problem by breaking it up into smaller ones and solving each of the smaller ones separately, either in parallel or sequentially. The logic behind decomposition is to solve iteratively the large-scale complex mixed-integer problems, which can not be efficiently solved altogether by the commercial solvers.
It separates the problem into two related problems (a master problem and subproblem) by classifying the constraints of the problem into “easy constraints” and “difficult constraints”. The master problem typically contains discrete variables with “easy constraints” and provides an upper bound for the original problem. The “difficult constraints” are moved to the subproblem, which gives a lower bound and generates Benders cuts for the master problem. These two problems are solved iteratively in a delayed-constraint-generation fashion and finally, converge to a globally optimal solution.
On the sideline, decomposition has some benefits, especially when there is some coupling or interaction between subproblems and with the master problem such as in the case of market and trading problems. This interaction can be effectively modeled using this decomposition in many problems.
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I need code of Consensus + Innovations and OCD in any programming language preferably Matlab or R
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Aamir Nawaz, Can you provide code for Consensus + Innovations and Optimality Conditions Decomposition?
I would appreciate it if you help me.
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I have Co/Al2O3 catalysts and carbon is deposited on the surface by decomposition of light hydrocarbon on the surface of catalysts, therefore the catalysts are containing cobalt carbides and some deposited carbon on the surface. By increasing the decomposition temperature, the content of carbon on the surface of the catalyst increased and the G and D bands were observed, while for the other samples (with lower gas decomposition temperature) there is not any G and D bands, while the 2D band with lower intensity and broader was observed in these samples. According to our XRD analysis, for the samples prepared at lower decomposition temeprature (No.1, 2, 3, 4) without G and D band and with only weak 2D band at 2670 cm-1, we have some cobalt carbides species, while for those with G, D and 2D bands (No. 5, 6) there was not any peak belong to cobalt carbides in XRD spectrum. I would like to know your opinion about the band at 2670 cm-1 in these Raman spectrums.
Thanks in advance.
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For defect-free graphene or nanotubes, you can have a 2D mode without a D-mode because the D-mode is symmetry-forbidden without defects while the 2D-mode is symmetry-allowed both for defected and undefected material.
However, if a G mode is absent, I would be very careful to claim something is a 2D mode.
In the case of your spectra, it is hard to tell what kind of physics is going on for spectra 1-4. That feature is not really a sharp peak as you would expect from a regular Raman process.
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Let us discuss about the advantages, disadvantages, and use of powerful decomposition techniques like Bender's decomposition for large-scale optimization. I invite my esteemed colleagues and researchers to share important literature, ways of implementation, and potential application areas of decomposition algorithms, in this forum.
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Dear R.K
You are right, we can't say no, because we don't know about new developments.
Probably, one of the reasons by which Bender's decomposition technique has not been applied to MCDM - and I share your opinion about its application - is because problems in MCDM are systems, and like that, they can't be partitioned, other than for study.
Your last paragraph resumes the same point, better than my sketchy explanation, so, we agree
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Dear Researchers,
The overall cost of "my algorithm" is dominated by finding orthogonal basis, which costs (M p.^2) where p is less than M , for the input matrix. My concern is: is there nay alternative method (or low-cost QR decomposition) to find the orthogonal basis with lower cost, please?
Thank you so much for your consideration in advance
Best regards,
Bakhtiar
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The error rate of tensor (CP) decomposition returned by python module tensorly is 0.4 or 0.9, is it satisfying? What is your advice to decrease error in tensor (CP) decomposition or matrix decomposition?
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Proper designing of decomposition apparatus
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Is there any big difference between 2-butanone and ethanol? I see that boiling points are similar, but I would like to know if some other characteristics (kinetics or decomposition behavior) are important. Thank you bery much¡
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Thank you¡¡¡
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Our time series dataset have sparse multivariate variables, and need to be classified by unsupervised clustering. Since the sparse nature of dataset, we plan to use matrix/tensor decomposition. However, the date of each sample can not be binned or matched. Could you kindly suggest a decomposition method can be used in non-matching time series data?
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What about filling the data gaps in the multivariate dataset? As done here:
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Following an incident I investigated where a body was discovered in the same room as a small fire. The cause of death was undetermined, due to advanced decomposition. There was no evidence of the body being damaged by fire. It is believed the death occurred approximately 10 months before discovery. The body was found in the reclined position with the upper half of the body in advanced stages of decomposition. However, the lower half still had areas of intact tissue. So I am interested in the likelihood of analysing the blood in the remaining tissue to determine if carboxyhemoglobin was present to evaluate if death was caused as a result of the inhalation of fire fumes.
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Also check please the following useful RG link:
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Anaerobic decomposition or aerobic decomposition with the help of epigeic earthworms which one best method for organic waste decomposition?
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It depends on your experiment objectives and targeted end products. If your primary goal is volume reduction and desired end product is compost then go for aerobic digestion. However, if you are opting for energy production and waste stabilization then go for anaerobic digestion. Besides, you have to consider the optimum temperature condition (i.e.mesophilic, or thermophilic) for epigeic earthworms to decompose the organic waste as well.
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Good evening please I need help, I am working on the reduction of hygrothermal models using proper generalized decomposition.
I would like to have a document that explains this method
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Reduced order models (ROMs) are simplifications of high-fidelity, complex models. They capture the behavior of these source models so that engineers can quickly study a system's dominant effects using minimal computational resources.
Regards,
Shafagat
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We know that LU decomposition is an important method for stochastic simulation of 2D RF. Assume the covariance matrix of regionalized RVs is C, it can be decomposed as C=LU according to the LU algorithm, then a RF can be generated by X=L'*y, where y is a vector consisting of independent standard normal random numbers. I want to know whether can I use LU decomposition for simulation if n observations exist as the conditioning data? If so, how can it be demonstrated?
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Thare are many decomposition types, Why you do not try another of what you applied before
regards
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Which method more suitable for decomposing of organic waste and recycle them.
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There are a lot biocomposting methods for waste degradation. You can:
1. Use Trichoderma. Trichoderma serves as a compost activator. It helps to decompose agricultural wastes and increase the nutrient content of compost.
Here are some useful material:
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Wavelets are a set of mathematical functions used to decompose a signal continuously into its frequency components, the resolution of each component being equal to its scale.
A wavelet transform is the decomposition of a function based on wavelet functions. wavelets are transmitted and scaled samples of a function with finite length and highly damping oscillation. Compared to the Fourier transform, it can be said that the wavelet has a very good localization property.
For example, the Fourier transform of a sharp peak has a large number of coefficients, because the basic functions, the Fourier transform, are sine and cosine functions whose amplitude is constant over the whole interval.
Wavelet functions, on the other hand, are functions in which most of their energy is concentrated in a small interval and diminishes rapidly. Therefore, with proper selection of mother wavelets, better compression is performed compared to Fourier transform.
The mother wavelet is horizontally and vertically deformed through the effect of the signal.
The wavelet coefficients, which are equivalent to the Fourier decomposition amplitudes, are thus a measure of the correlation between the signal shape and the contour of the deformed mother wavelet that follows the signal.
As wavelets are constructed over a scale change operator, we can better understand their effectiveness using a fractal analysis, and more generally using any multi-scale approach.
They should become an incontrovertible tool across the whole of scientific geography, with its interest in multi-scalar and multi-scale phenomena.
More specifically, the signal − whether it is a chronicle series or an image − is decomposed into one general part and some details representing some irregularities.
The general part is then itself decomposed into a new general part and more details, and so on. This is an iteration model similar to that of the construction of a fractal.
This connection explains the effectiveness of wavelets in the study of fractals.
What other characteristics of wavelets can be used in fractal analysis?
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According to the following discussion, discontinuity in wavelet signals can be considered as a kind of fractal.
In the figure below, how does this discontinuity in the signal contribute to fractal analysis?
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Can You please help me out on how to select a wavelet for ecg datasets
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MATLAB has a function which decomposes time-domain signals fully automatically, including into wavelets. It is in with their "toolkit" for A.I. on
signals. Beyond converting the data into wavelets, it also identifies which
components of the signal hold all of the information.
They have some demo lectures on it
Nominally, it is a commercially sold product, not free. But virtually any of their A.I. products can be had as demos for free.
If nothing else, try to locate the training videos, to get a sense
of what good advanced tools can do. It is important to decide
whether you want to do a lot of your own mathematical
programming, whether you want to leverage your work
with existing software libraries, or whether you want to
try to use a fully-integrated product. All are fully viable
approaches.
It is also worth clarifying in your own mind - do you want to
use wavelets simply as a denoising step before other
processing, or do you wish to do broader processing
and signal analysis based on wavelets. Once again,
both answers are totally reasonable.
Good luck!
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Hello everyone,
Can someone please let me know what does "ensemble average for a given window of pixels" mean when calculating a coherency or covariance matrix? I have taken this sentence from a paper "Polarimetric Target Decompositions and Light Gradient Boosting Machine for Crop Classification: A Comparative Evaluation".
According to my understanding I have to consider a window of size m x n and take the pixels of a radar image in that window and then perform ensemble averaging i.e. mean of those pixels. Please let me know whether my understanding is correct or not.
As of now I am performing a 2D convolution with a square window and varying their size to analyse the performance.
Thanks in advance.
Best regards
Pavan Kumar.
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Dears Pavan and Sriram,
I have just arrived now to the same question. In some papers it appears the next operations for sentinel 1:
r = { |VV||SVH|}
where |x| means the modulus and {x} means ensemble average.
If I am working with GRD sentinel 1 image. I would take the absolute value of each band -VH and VV respectively- but from that point I do not know what to do as averaging VH and VV pixel by pixel sounds a bit rare to me.
What am I misunderstanding?
Kind regards,
Jaime
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Dear colleagues:
I am interested in this topic because I want an organism that consumes food waste at a high rate and the data for insects and worms seem more homogeneous. I have to admit that terrestrial isopods have me completely surprised. Some species reproduce at much higher rates than other invertebrates. However, the data in the literature speak of very low daily intakes of less than one mg per g of live weight. On the other hand, as they live at overcrowding levels of tens of thousands per square meter they could compensate this low feeding rate. Even so, it is not clear to me. The species that I keep in the laboratory as a companion to the terrariums is Porcellio laevis. I don't know if I have minimized the effect of terrestrial isopods as detritivores. I know that isopods crush the food considerably and help the bacterial processes of decomposition. I do not care whether they degrade directly or indirectly. I want to know their exact contribution and I repeat, the results are very disparate and confusing. For example in these papers:
Effects of Terrestrial Isopods on the Decomposition of Woodland Leaf Litter Author(s): M. Hassall, J. G. Turner and M. R. W. Rands Source: Oecologia , 1987, Vol. 72, No. 4 (1987), pp. 597-604.
Abd El-Wakeil, Khaleid. (2015). Effects of terrestrial isopods (Crustacea: Oniscidea) on leaf litter decomposition processes. The Journal of Basic & Applied Zoology. 69. 10.1016/j.jobaz.2015.05.002.
These studies report composting rates of more than 70% of the biomass ingested (~millipedes), which is logical if we look at their diet. But the most surprising thing is that they also talk about feeding conversion ratios (FCR) between 1.5 to 2, which would place them at the same level as the tenebrionidae. I would like to set up a discussion on isopods can be used on an industrial scale to firstly degrade waste and secondly to compost. The thousands of isopods I have in my lab inside terrariums don't seem to be effective enough to attract attention. Judging by their numbers the breeding conditions are appropriate. In short: I don't know what to think of isopods. I guess I'll have to do a lot of tests before I decide.
Any suggestion?
Thanks
****************************************************************************
Daniel Patón. Numerical Ecology. Ecology Unit
Department of Plant Biology, Ecology and Earth Sciences
Faculty of Sciences. University of Extremadura
Avda. Elvas s/n 06071 Badajoz (Spain)
****************************************************************************
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Daniel; The only conditons that I pay any attention to are;
1. Well aerated.
2. High humidity but not saturated.
3. Unprocessed material is thick enough for it to be dark at the isopod layer.
Cheers, Jim Des Lauriers
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I intend to use Adomian decomposition combined with Laplace transform method, I am having issue to interprete the conditions as attached herewith.
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I can not give the code
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I am trying to activate HA with PEI at high temperatures but PEI will decompose at 180°C, it there any kind of reticulation method or ... to increase the thermal stability of PEI?
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There are several methodologies to improve the thermal stability of thermoplastics including processing in inert environments to prevent oxidative chain scission reactions, increasing the molecular weight to reduce chain mobility, and incorporation of blends. Unfortunately, most polymers will have degraded substantially by 600 C, and in the case of PEI there are methly linkages along the chain that will decouple, irrespective of the modifications applied, around 200 C.
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Hello,
The AIBN in our lab is purchased from Sigma Aldrich and dissolved in acetone at 12 wt %. Does this still need to be recrystallized before use in a free radical polymerization or are the effects of decomposition lessened by its presence in the solvent?
Thanks
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Purchase Sigma-Aldrich "755745 recrystallized from methanol, 99%." Most probably they sell solution for a convenience of the user.
Sometimes it is difficult to dissolve a solid in a solvent. A solution of AIBN can be mixed with another solvent. If one does not need acetone, it is possible to evaporate it carefully. AIBN can explode.
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Combination reactions can be exothermic or endothermic, but are more often exothermic. Decompositions reactions are therefore mostly endothermic. What is the pattern for combination reactions that are exothermic, and endothermic?
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Alexander yes, you said something about the coefficients too. So Gibbs calculations alone doesn't answer, I need to find an example where the same equation but different coefficients change the outcome of H or S.
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In the case of decomposition based MaOPs, for example NSGA3, some predefined Ref.Points are associated to the population members in order to decompose a Many Objective problems to the series of multi/single objective problem!!
so how it works??
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The Ref. points or vector which are also in some cases different with each other, decomposes the objective space with the use of vectors from the origin to the desired point.
So while the algorithms is being ran, the population members gather around their own associated Ref.point so each Ref. point make some particles just to search the area around it in order to enhance the diversity of the population!
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what ingradient, any pH, medium,decomposition temperature,
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If you want to remove that thin film of MgO from stainless steel use toothpaste (Colgate). :)
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I am working on a project which is about clustering the time series signals. I wanted to apply some smoothing or compression signal to remove unimportant shruggs and spikes from the signals. I learnt about the Wavelet Decomposition which compresses or stretches the signal can anyone help me about the implementation of this python ?
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There are many wavelets that can be used for time-frequency analysis as you mentioned. The selection of the wavelet is very important because inappropriate selection can lead to undesired biases in the time-frequency spectrogram OR time-scale scalogram. The Morelet wavelet is a commonly used wavelet in many applications as it optimizes both time and frequency resolutions of spectral peaks in the spectrogram. For that reason, the software packages that I suggested currently support only the Morelet wavelet.
I refer you to the references below for the use and properties of other wavelets:
1) S. Mallat, A Wavelet Tour of Signal Processing, The sparse Way, Third Edition 2009
2) Charles Chui, Wavelet Theory, Academic Press, Cambridge, MA, 1991.L.
3) Daubechies, Ten lectures on wavelets, in SIAM, Philadelphia, 1992.
4) E. Hernandez, G. Weiss, A First Course on Wavelets, CRC Press, 1996.
5) C.S. Berrus, R.A. Gopinath, H. Guo, Introduction to Wavelets and Wavelet transforms A Primer. Prentice-Hall, Upper Saddle River, NJ, 1997.
6) C.K. Chui (Ed.), Wavelets-A Tutorial in Theory and Applications, Academic Press, Cambridge, MA, 1992, pp. 15–50.
7) G.S. Goswami, Chan, Fundamentals of Wavelets, Theory, Algorithms, and Applications, John Wiley & Sons, New York,1999.
8) Stephane Jaffard, Yves Meyer, Robert D. Ryan, Wavelets, tools for science and technology, in SIAM 2001, p. 256, ISBN: 0-89871-448-6.
You can also check the MathWorks for the description and implementation of various wavelets:
Hope this helps!
Best regards,
Ebrahim
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Vitamin C (Ascorbic acid) when oxidized will create brown decomposition. But it is used as an antioxidant excipient in pharmaceuticals or an anti-brown substances in fruit & vegetable. Does its brown decomposition affect the appearance of the drug solution or create its own brown in fruit & vegetable. Could anyone having experience give me opinion about these applications of Ascorbic acid ? How can we prevent brown colors created from Ascorbic acid.
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According to the following link, vitamin C serves as a reducing agent and reduces iodine to iodide ions (colorless in solution)...So, if vitamin C is present, the brownish color of the iodine solution will become colorless:
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I want to blend HDPE(BL3) with PA6 to improve its barrier properties with extrusion molding process. this product need to be white and shiny but when i blend these, yellowing occurs !
what is the problem?
HDPE decomposition?
morphology?
Mold Tempreture?
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you can compare TGA graph for this blend and pure HDPE & PA to mold temp or extrusion.
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I am examining the decomposition of the forecast error, but in my chart you can see that the largest share is the variables that, according to Granger, are not even the cause of the variable. So what is the relationship between the two studies (Granger and FEVD)?
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Abolfazl Ghoodjani it is Gretl
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Based on a resent question; what is the difference between a saprophyte and a saprotroph?
In Greek saprophyte would be saprós (“putrid; decayed; rotten”) and phyte ("plant") thus meaning a plant that will live of dead or decaying organic matter. Saprotroph on the other hand, would be saprós (“putrid; decayed; rotten”) and trophē (“food; nourishment”) and thus include all organism with this lifestyle.
It seems as if the term saprophyte would be incorrect as plants are in actuality not saprophytic. The same problem comes in with saprophytic vs saprotrophic. My concern is this, why were we taught that "saprophytic" or saprotrophic fungi are saprophytes as this would seem to be incorrect. Recent publications and textbooks still refer to saprophytes. Has the term saprophyte been abolished or regardless of the difference we now consider saprophyte and saprotroph as synonyms?
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Just now, both terms saprophyte and saprotrophic are be used in the field of fungi papers. So, both terms refer to fungi which feed and grow on dead things such as: plant debris, organic materials, dung etc.
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I'm currently working on acoustic denoising algorithm in leakespecially different type of wavelet shrinkage and other sparse component decomposition. I'm working on a dataset of real-life mesurements and I'm looking for indicators that describe a good denoising such as MSE, SNR... But those rely on the knowledge of a perfectly denoised signal or at least some knowledge about the signal you are looking for which I don't have since I only got access to the noisy signal.
Do you have some suggestions of performance indicators that could evaluate the quality of the denoising without relying on the knowledge of a denoised signal.
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Hello everyone!
I am looking for a way to analyze the interaction of a gas with the adsorption site of a solid.
SAPT seems very attractive for non-covalent interactions but when the adsorption site contains a transition metal, covalent phenomena may occur.
So is there any reliable method that can account for covalent bonding?
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You should mention adsorbate and adsorbent -
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when I analyse the solution of dynamical system(in time series) by wavelet decomposition, how can I distinguish the differences in figures d1,d2,...,d5?
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Wavelet decomposition uses a representation similar to x = sum on i=1...N of (x(i).e(i)), where e(i) would be an orthonormal basis.
So, it's a linear space decomposition, along N (or infinite) dimensions.
That's your starting point.
Look at the e(i), then project on the sub-linear space e(1),...e(n) for n less than N.
With a mathematical eye, it's going to be smoother for you to grasp what you get...
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The analysis of electrocardiogram (ECG) signals allows the experts to diagnosis several cardiac disorders. However, the accuracy of such diagnostic depends on the signals quality. In this paper it is proposed a simple method for power-line interference (PLI) removal based on the wavelet decomposition, without the use of thresholding techniques.
A Matlab code for power-line interference removal is available in: https://github.com/brunobro/power-line-interference-removal-in-ECG.
I request the evaluation of fellow researchers.
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Dear Researcher
I wish the best for you with Regards
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Wavelet is a function that is localized in time and frequency, generally with a zero mean.
It is also a tool for decomposing a signal by location and frequency.
Wavelet decomposition is original in two respects relative to Fourier decomposition. On one hand, sine and cosine functions, which are periodic, are replaced by a mother function, which is quite regular.
The mother wavelet is horizontally and vertically deformed through the effect of the signal. The wavelet coefficients, which are equivalent to the Fourier decomposition amplitudes, are thus a measure of the correlation between the signal shape and the contour of the deformed mother wavelet that follows the signal.
the signal − whether it is a chronicle series or an image is decomposed into one general part and some details representing some irregularities. The general part is then itself decomposed into a new general part and more details, and so on. This is an iteration model similar to that of the construction of a fractal. This connection explains the effectiveness of wavelets in the study of fractals.
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Any probable technique or catalytic agent to degrade the plastic material without polluting environment? Kindly share your opinion or any article related to this.
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Hello everyone,
I have modelled the optimization problem to minimize the distribution system losses and modelled it as a mixed-integer second-order cone programming(MISOCP) problem. I used several well-known solvers such as GAMS-MOSEK/GUROBI/CPLEX to solve it, but they cannot solve it in 24 hours or higher time. I want to apply benders decomposition or some other approach to solve the problem within 2 hours.
Please suggest some references to learn benders decomposition for MISOCP type problem or some other approach to solve formulated MISOCP problem in less time.
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I think yes
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I want to compare accuracy among these four methods in terms of reconstruction. These four methods are mentioned below:
1. EMD (empirical mode decomposition)
2. DMD (dynamic mode decomposition)
3. QN (quasi newton method)
4. GAN (generative adversarial network)
It would be highly appreciated if anyone provides detailed explanation along with some publications.
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Thanks for clarification. Now, I am concerned about non-Euclidean system. Is DMD enough to handle non Euclidean system if we tend towards reconstruction accuracy? Real system is not like plane or surface which is Euclidean in nature. Do we need to incorporate geometric deep learning to retrofit DMD if we want to reconstruct accurately from a corrupted system? Or we need to blend both DMD & geometric deep learning to fully exploit high resolution spatio- temporal data from a non Euclidean system? Please provide clear explanation .
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M project requires me to decompose a time series using empirical mode decomposition and its variations and group the resulting components into high frequency, Low frequencies and trend.. The next step is use a machine learning algorithm to forecast each category and use another machine learning algorithm to to get the final forecast.
Any resources in PYTHON OR R will be greatly appreaciated
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How can we compute the correlation coefficient if the original signals(s) are significantly positively correlated with the approximation coefficient series (a1, a2, a3, a4, a5) in the wavelet decomposition and reconstruction of a specific signal?
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It is just like a auto correlation of signal. You can verify it by CWT instead of DWT. The CWT function is available in MATLAB. The length of coefficients are equal in all decomposition levels. It is redundant wavelet decomposition or CWT.
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In designing an experiment to investigate regional influence of these elements (temperature, humidity) on decompositional stages and insects colonization of pig carcasses, how would a control be setup for the elements given its uncharacteristic nature to be carried out in a laboratory?
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Hi. I hope the folloeing article website help you:
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I want to decompose some sensor data using wavelet. The FFT shows that my data does not contain higher frequency component(It has an influential DC component). Therefore which mother wavelet would be appropriate for decomposition?
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There are many wavelets, and to choose the correct wavelet, you need to consider the application you are going to use it for. I hope this discussion will help you :).
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Hi all I have now finished drafting my article on the importance of soil to forensic science, if anyone has anything that is relevant to soil and decomposition that can be included within my final type up please let me know and I will include a citation of your help. thanks
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My team has been collecting leaf litter annually over the past 10 years for quantification of the leaf primary productivity of our study site. We put aside dried samples of the litter every year, stored them in a cool and dry place (in closed plastic tube), but we are just about to analyze their elemental composition.
I would like to know whether there is a possibility that the elemental content modified over time due to decomposition of the litter. I would say "mostly no" because the biological activity must have been very low in these dry samples, but I cannot find papers documenting this.
Could anyone help on this aspect? Thanks in advance.
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The nutrient content of dry leaves might be changed over time naturally. We have to take in mind that everything is changeable over time. It may be happened due to weather (temperature, rainfall, humidity, etc.) fluctuation from hour to hour, day to day, month to month ......... That is why nutrient content would be fixed for a long time even in dried leaves.
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Dear colleagues,
i am looking for the package or command, which performs times series decomposition in STATA. So far I did not find anything. Example can be found here: https://towardsdatascience.com/an-end-to-end-project-on-time-series-analysis-and-forecasting-with-python-4835e6bf050b at figure 5.
Look forward to valuable comments)
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Dear Mousumi Bhattacharya , thank you for your help!!
Dear Kehinde Mary Bello and Olumide Olaoye , Mousumi Bhattacharya has helped me with Unobserved-components models, which, as far as i understand, help to decompose into trends and cycle components. However, if you know any other options for positive and negative shocks decomposition (apart from impulse - response functions), i will be happy to hear for them. Especially for some references on STATA implementation of them.
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In some cases concerning the treatment of sludge by means of microwave irradiation, what is the reason for the presence of more decomposition of organic materials at lower temperature rates compared to high temperature?
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I think it can be that the reaction rate at first increases by the temperature reaching maximum at certain temperature and then slow down because of the depletion of the reactants. That the decrease at higher temperature is caused by the depletion of reactants.
Then I think you have to study the reaction considering my expectations.
Please for more information please refer to the link:
Best wishes
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When a surface wave is superimposed over turbulent current, a periodic velocity fluctuation is observed and the conventional Reynolds decomposition of the velocity field is not satisfactory and phase-averaging of the velocity signal needs to perform why?
Why phase averaging is necessary for such type of flow?
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Dear Professor Denaro
Thank you very much for your explanation. Yes, I am not talking about decomposition's validity, and I am fully convinced of your explanation. However, I have one more issue on my question, for e.g., the decomposition of velocity, u = u1+u2+u3, where u1, u2, and u3 are the averaged-velocity, turbulent fluctuation, and periodic wave velocity respectively. For the calculation of turbulence statistics of such flow, we have to remove wave velocity from the turbulence by ensemble phase-averaging. My concern is why this is necessary to do the phase-averaging. We can easily compute the time-averaged turbulence statistics with this wave component.
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I am working with the hourly electricity spot price data, due to the large dimensionality I convert the discrete data into functional data. The model I use the functional autoregressive model of order more than one, as per my knowledge there no R package available to deal with such model, so I apply an alternative method, using the functional principal components (FPC's) as dimensional reduction, utilizing the associated principal components for the forecasting through multivariate time series model. Then I convert these forecast scores into functional curves through Karhunen-Loeve decomposition into a functional form, in such a way I obtained a forecast of each day as a single curve. Know, to check the accuracy of the model I want to calculate percentage mean square error or mean absolute error. know my problem start from here, So I want to reverse back each curve into 24 discrete points, is there is any package in R which is helpful in dealing with such a problem.
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As I understand, the accuracy will depend on a number of factors, including the forecast horizon. Also, the metrics you mentioned (such as the MAPE) may not be the best choice for your task. Please let me recommend this detailed guide for checking forecast accuracy:
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Hello,
using Cholesky decomposition in the UKF induces the possibility, that the UKF fails, if the covariance matrix P is not positiv definite.
Is this a irrevocable fact? Or is there any method to completely bypass that problem?
I know there are some computationally more stable algorithms, like the Square Root UKF, but they can even fail.
Can I say, that problem of failing the Cholesky decomposition occurs only for bad estimates during my filtering, when even an EKF would fail/diverge?
I want to understand if the UKF is not only advantagous to the EKF in terms of accuarcy, but also in terms of stability/robustness.
Best regards,
Max
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If I understand your question correctly, it concerns not the initial covariance matrix rather the updated covariance matrix you get at the end of each Kalman iteration.
If such a condition arises you may use Higham's method to find an approximate positive-definite covariance matrix.
Reference:
Computing a nearest symmetric positive semidefinite matrix - ScienceDirect
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Can you always say that the upper bound obtained in Benders decomposition is better than the upper bound in the Lagrangian relaxation method (minimization) and the lower bound vice versa?
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Thanks.
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I ask for some help with the energy decomposition calculation by mean of gammess (or another) software. I am studying a complex and I need to know the magnitude of the electrostatic component.
Obviously, in the manuscript, we will recognize this collaboration.
Looking forward to any collaboration,
My sincerely,
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Dr. hay un método en la página del NBO que puede ayudarte. Aislan la interacción cis y la trans en un complejo metálico planar cuadrado ya que inicialmente la energía de ambos es la misma y no deberías ser así. Puedes también producir archivos del .31 al .41 en el Gaussian con la opción pop=nboread y al final $NBO PLOT FILENAME=EDGAR $END. Luego usas el Chemcraft para abrir el .31 y se cargan todos los demás y podrás leer los orbitales atómicos, los híbridos, los moleculares y los nbo (también puede abrir un fchk). Vas a la opción tools y busca en la opción orbitals la herramienta de analizar con la que podrás descomponer las energías en muchas formas y ver si encuentras la información que buscas según el modelo orbital. El componente electróstatico debería poder leerse de alguna forma de la matriz de Fock ya que ahí se pueden separar las interacciones pi, las covalentes y representar la estructura de un cloplejo como una representación de Lewis. Cualquier cosa no me consultes, busca que si se puede!
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can anyone please help me, how to implement the CORDIC algorithm for eigenvalue decomposition using the Jacobi method?
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Hi
in a traction compression uni-axial test on cylindrical samples, I use a set of 3 extensometers spaced at 120° around the sample to obtain the average deformation of the cylinder. this allows me to determine the stress and strain tensor in the sample. now, if I decompose the cylinder in tree equal sector cylinders (decomposition along the axe of loading) is it possible to obtain the stress and strain tensor of each sector cylinder from the stress and strain tensor of the hole cylinder?
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Dear Mohamed,
I don't think that what you suggest will be possible. Given the fact that an asphalt mix is not really homogenous what is "proved" by the differences in the values of the 3 LVDT's. Personally I think that the best way to deal with it, is trying to keep the largest LVDT value constant (in order to get a strain controlled test) and accept that sometimes (hopefully only a few) the increase in one of the other two LVDT's becomes larger than the target value of the third one.
Regards
Ad
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I am working on single trial motor imagery data i.e. EEG data. I am following a paper which has a dataset from BCI challenge IV (dataset 2b). After removing noise and extracting all the data from files into matrices, I am doing frequency band separation using wavelet decomposition(discrete wavelet transform) for frequencies 8Hz to 30Hz. after using dwt2 (2d wavelet transformation) I get four values LL, LH, HL, HH (L=LOW, H=HIGH). I want to confirm are these 4 combinations alpha band, beta band ,gamma band and delta bands? I cant find this anywhere.
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For the wavelet decomposition problem I found python wavelet transformation library "pywt" (Link: https://pywavelets.readthedocs.io/en/latest/) it contains for both 1D and 2D wavelet Decomposition. Also many wavelet decomposition families I used Daubechies of order 4. For the 4 level decomposition I used this function of pywt.dwt2 4 times to get to my results. All for wavelet decomposition could be found in this Library
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Any technique could detect the degree of litter decomposed by microbes? Or any indexes could do this job? I want to split the contribution of microbes during decomposition, so any suggestions are appreciated.
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Dear Dr. Sen Yang ,
See the work below. The authors used DNA-SIP to analyze the microbial community associated with sugarcane via assimilation of 13C by microbial cells. It is not quite what you intend to do, but it can give you insight into how to do your research.
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To maintain the proper crop plan most of the times there is not enough time to make the field ready for the next crop.
In this particular context , can bio-decompser be a solution? What about time management? How long it takes to decompose the materials? What about the economics?