Science topic

Graphs - Science topic

Graph Theory is a branch of combinatorics, here we discuss the theory and application of graphs.
Questions related to Graphs
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It is well recognized that hypergraphs can be represented as factor graphs to some extent.
But something plagued me is that, when converted to a factor graph, how is the degree of a node in the factor graph calculated? For example, when a node i in a factor graph is connected to a factor node with cardinality 5 in a hypergraph, is the degree of node i considered as 5? Or is it regarded as 1?
Can anyone explain this for me? I appreciate it a lot. And thanks for your time.
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In your example, the degree is 1.
For hypergraph, the degree is just the number of hyperedges the node is incident to, which is equal to the degree of the corresponding node in the factor graph. In the factor graph, you may also consider the degree of factor nodes, which follows the normal definition of degree for ordinary graphs.
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I have performed 3-point bending on steel beam with 20*20mm square hollow section. I had obtained the Force-displacement graph for the experiment. I am trying to simulate this experiment in Abaqus Dynamic EXPLICIT.
For material model, I have used yield stress-plastic strain data. Element type used is C3D8R and three elements are used per thickness. The loading rate is increased to 1 m/s within the first 10 millisecond and thereafter it is maintained constant. Kinematic contact method is used to define the interaction between roller and beam. Also, considering the symmetry of the model, I modelled only quarter section ( force was multiplied by 4 times ). Symmetric boundary conditions were applied
The values for Force Displacement curve in simulation comes considerably lower than actual values. What could be the possible reasons for this ? How can I rectify this error?
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To get better simulation results, stress strain behaviour of material should be same as tested in the lab. Standard material models will lead to large variation in results. With your input for 'yield stress-plastic strain data', is it containing strain-hardening beyound yield ? That should be given as input from physical tests of the same materisl used for 3 point bending.
Second issue: 3 point bending is used for solid sections, where worst effects, say maximum bending with large shear force at the loading point occurs. This test may not give good results for hollow box section. Are you following any ASTM or other test method (as recommended) ?
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A DMA graph of a thermoset polymer gives the storage modulus graph, loss modulus graph and a Tan (delta) graph. Tg of the polymer can be either Storage onset temperature or the Tan (delta) peak temperature in most cases.
In the case, the question is, how can we explain the relationship between half peak width (glass transition)of Tan(delta) and the network structure of the polymer. Can someone explain?
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I would say that width of Tan D peaks in DMA is related to distribution width of the associated relaxing elements. In the case of glass transition, relaxing elements are mobile chain segments in amorphous regions. The wider is the distribution of the segments in terms of their mobility (length, rigidity, packing density, free volume, intermolecular interactions etc.) the wider is the DMA peak. Accordingly, widening of the peak in crosslinked systems may indicate nonuniform crosslinking structure: presence of domains differing in the crosslinking density (length of the segments between the crosslinks).
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\textbf{MIZAN TEPI UNIVERSITY\\}
\textbf{COLLEGE OF NATURAL AND COMPUTATIONAL SCIENCE\\ DEPARTMENT OF MATHEMATICS\\Mathematics for Natural Sciences(Math1011) \\Final Exam for First Year Regular Students.~~~~Total mark:~~~~40\%~~~~~ \today}
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\question Composition functions are always commutative, meaning \( f(g(x)) = g(f(x)) .\)
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\question The graph of $y=sin(x)$ is an increasing function on $[\frac{3\pi}{4},\frac{5\pi}{4}]$
\question Every one to one functions has an inverse.
\question The simplified form of $\log_{5}^{(\log_{3}243)} =1$
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\question If \( f(x) = x^2 \) and \( g(x) = \sqrt{x} \), then \( (f \circ g)(4) \)=.
\question The domain of the function $f(x)=\sqrt{4-x^2}$ is=\dots\dots
%\question If $g(x)=2x+1$ and \( (f \circ g)(x) \)=$12x^2-2x-9$,then the function $f(x)$=
\question The value of $tanh(\ln3)$=\dots\dots
\question Suppose $f(x)=9-3^x$ ,then $f^{-1}(x)$=\dots\dots
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\question Consider $f(x)=\log_{5}^{(x+4)}$, ~then which of the following is~\underline{Not true} about the graph of $f(x)$?
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\CorrectChoice The y-axis is a vertical asymptote of the graph of $f(x) $
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\choice domain is the set of real number
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\question Let $h(x)=4^x$,then show that $h(x+2)=16h(x)$.~~$\dots(2pts ) $
\question Find all solutions when extracting the $3rd$ root of the complex number $z = 4i$.~~$\dots\dots\dots(4pts ) $
\question Find the point $p(x_0,y_0)$ that divides the line segment $AB$ joining points $A(2,3)$ and $B(7,-2)$ in the ratio $2:3$.~~$\dots\dots\dots(4pts ) $\\
a. ~Does the point $p(x_0,y_0)$ lie on the line $L:x-5y+15=0$? ~~ \\b.~Find the distance between $p(x_0,y_0)$ and $L:x-5y+15=0$ ~~
\question Let $g:\mathbb{R}\to \mathbb{R}$ defined by $g(x)=\sqrt[3]{x+1}$, then show that $g(x)$ is a one to one correspondence. ~~$\dots(4pts ) $
\question If $f(x)=\frac{3x+4}{x^2-9}$,~then find ~~$\dots\dots\dots(4pts ) $
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\item[a] the domian of $f(x)$
\item [b] the x-intercept and y-intercept of $f(x)$
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\item[d] Sketch the graph of $f(x)$.
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\section*{Bonus(3\%):Sketch the graph of $f(x)=2-2^{-x}$,then discuss the domain,range,intercepts,and asymptetes clearly and correctlly.}
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You can get full information on how to write any exam within LaTex at : https://www.overleaf.com/learn/latex/Typesetting_exams_in_LaTeX
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Dear all,
I conducted an oddball task to observe the p300 response, and I have a couple of questions:
1. I would like to inquire whether my ERP graph is meaningful.
2. Why does the brainwave response to the standard stimulus exceed that of the deviant sound?
3. I find these graphs rather complex. Could I receive some advice on how to create clearer ERP graphs? I created them using Matlab.
Your insights would be greatly appreciated!
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Hi dear
Great job! You have accurately captured the P1, N1, and P2 components that are associated with the physical properties of the stimuli. Your deviant sound has resulted in delayed discrimination (N200) and categorization (p300) of the stimulus. However, overall, there are no unusual issues in your data. For greater precision in determining component onset time, I recommend utilizing the grand average feature available in the EEGLAB software.
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Dear Technical Supporter,
My paper "Observations on graph invariants with the Lovasz ϑ-function" has been published in AIMS Mathematics, and I updated the PDF file and also added a doi link. However, Research Gate does not allow me to modify the status from Preprint to Article with the name of the journal. Could you help me please ?
Best regards,
Igal Sason
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Dear Rob Keller,
Thank you very much for your detailed response and advice.
Best regards,
Igal Sason
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Hello, I have the results for scattering rates, from epw software, but am wondering how I can plot the graphs of scattering rates as a function of energy as we have in this paper fig 6(a). .kindalyshare some information.
Thank You,
# Electron linewidth = 2*Im(Sigma) (meV)
# ik ibnd E(ibnd) Im(Sigma)(meV)
1 2 0.74585345124266E+01 0.00000000000000E+00
1 3 0.74585345124268E+01 0.00000000000000E+00
1 4 0.74585347474930E+01 0.00000000000000E+00
2 2 0.69732345805421E+01 0.00000000000000E+00
2 3 0.73937712638922E+01 0.00000000000000E+00
2 4 0.73937714320523E+01 0.00000000000000E+00
3 2 0.56870328376178E+01 0.59380777038025E+01
3 3 0.72215714326816E+01 0.11854851602414E+01
3 4 0.72215715157624E+01 0.11854851602414E+01
4 2 0.39942422518922E+01 0.13872317960828E+02
4 3 0.69880162209008E+01 0.20934857870599E+01
4 4 0.69880162474195E+01 0.20934857870599E+01
5 2 0.22701285746477E+01 0.79408123683872E+01
5 3 0.67274356213107E+01 0.26055621742724E+01
5 4 0.67274356625937E+01 0.26055621742724E+01
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Hi Km Sujata,
When you calculate scattering rates using the transport module they will be printed in the file inv_tau.fmt. These scattering rates will be calculated for the temperature you set in the epw input file. You need to compute them for each temperature you're interested. Note that what they have in the paper are the lifetimes, which are the inverse of scattering rates. Also note that you have several scattering rates in that file and what they plot on the figure are average lifetimes, so you will have to average them accordingly to what you want to do.
Best,
Bruno
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NA
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A sudden rise (very high value of RMSD) was followed by a sudden fall (very little amount of RMSD) in the deviation when plotted on the graph.
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Hello All,
I want legends to be positioned below the graph (outside), but in two or three rows accordingly, such that they do not extend beyond the vertical boundaries of the graph. Can anyone please help with this?
Thanks.
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There are two main approaches to position legends below the graph (outside) in Mathematica:
1. Using PlotLegends with Placed
This method utilizes the built-in PlotLegends function and the Placed option for legend placement.
Here's how it works:
Code snippet
yourPlot = Plot[Sin[x], {x, 0, Pi}] legend = LineLegend[{"Sin[x]"}]; (* Create your legend *) finalPlot = Show[yourPlot, Legend -> Placed[legend, Below]] (* Place legend below *)
Use code with caution.
content_copy
In this example:
  • yourPlot represents your actual plot.
  • legend is created using LineLegend (or other legend types like PointLegend).
  • Show combines the plot and legend.
  • Placed[legend, Below] positions the legend below the plot area.
2. Using the PlotLegends package
For more control over legend placement, consider using the PlotLegends package:
Code snippet
Needs["PlotLegends`"] yourPlot = Plot[Sin[x], {x, 0, Pi}] legend = LineLegend[{"Sin[x]"}]; finalPlot = Show[yourPlot, Legend -> LegendPosition[{0, -1.2}]] (* Place at {x, y} coordinates *)
Use code with caution.
content_copy
This approach offers finer control:
  • Needs["PlotLegends"]` loads the package.
  • LegendPosition[{0, -1.2}] positions the legend's lower-left corner at {0, -1.2} coordinates.{0} represents the horizontal position (often left at 0). -1.2 places the legend 1.2 units below the plot area (adjust as needed).
Remember to replace yourPlot and legend with your specific plot and legend creation code.
These methods allow you to effectively position legends below your graph in Mathematica. Choose the approach that best suits your needs and desired level of control.
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Hello,
If we generate a graph in some typical software and then without changing proportions or scale can we modify it? For example I created a graph of rarity of zooplanktons. Can I add picture of the representative species as a reference or a modification or as an aesthetic value?
Since I am not altering scale, it should be valid for publication. Right?
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Я впевнена, що так, але чому це питання задається мені? Яке відношення ч маю до цієї тематики?
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What Stata command should I use for PSTR graph for transition function? To obtain a similar graph:
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I don't think Stata has built-in commands specifically designed for PSTR, so you may need to look for user-written commands (e.g. for 'pstr'), or manually set up your PSTR model and the transition function. But curious to see if someone knows a commandfor this!
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I want to calculate hosoya index of different family of graphs and i need any software for this. If any one can help me
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I've developed a program that addresses this problem using Python through transforming the condition of non-incidence to a number-theoretical problem. For example, if we're given an edge set of the graph: $E(G) = \{(1, 2), (2,3), (3,4), (4,5), (5,1)\}$. I simply defined a condition that it checks for the edges with no common vertex and through BSA from the independent edge-set of size one, so on and so forth.
For example: {(2,3)} is an independent singleton. The program then checks for any other edge in the edge set that contains neither 2 or 3 e.g. (4,5). Now it checks for another larger independent edge set. That is whether there is an edge that does not contain (2,3,4,5). The program will do this for every edge singleton. Some results involving the Hosoya index coincide with the results of my program.
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I am using a constant potential version of VASP (cp-VASP) for a restricted molecular dynamics simulation to study the dissolution process of Cu from the Cu(111) surface. Towards the later stages of the MD simulation, I observed a significant increase in the Gibbs free energy, and hydrogen atoms began detaching from water. Why is this happening? My simulation has not yet reached the target number of steps. Here is my plot, MD trajectory,and my INCAR. (Sorry, the previous graph of the Gibbs free energy was incorrect. I have uploaded the new one here.)Thank you in advance for your assistance
SYSTEM
ISTART = 0
ENCUT = 400
ISPIN = 1
ISMEAR = 1
SIGMA = 0.2
ALGO = VeryFast
ISYM = 0
LREAL = Auto
LWAVE = .FALSE
LCHARG = .FALSE.
NSW = 2000
NELM = 25
POTIM = 0.5
IBRION = 0
EDIFF = 1E-4
# MD Parameters
MDALGO = 2
SMASS = 0
TEBEG = 300 ; TEEND = 300
# VASPsol Solvent Model - This corresponds to water
LSOL = .TRUE.
EB_K = 80
LAMBDA_D_K = 3.0
# CP-VASP Parameters
LCEP = .TRUE.
NESCHEME = 2
CAP_MAX = 2.0
NEADJUST = 5
TARGETMU = -3.6
FERMICONVERGE = 0.05
# slow growth
LBLUEOUT =.TRUE
INCREM = 0.0025
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It depends on the algorithm to perform the time evolution, but usually this is a sign of too large of a time step. Energy conservation is not normally enforced in the numerical evolution. Remember further that DFT is a non linear problem so instability might be more subtle. As first test I would reduce the time step or check the time evolution algorithm.
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I have read many papers on working of electrochemical sensing of materials. Somewhere researchers plot i(current) vs. v^1/2(square root of scan rate) and somewhere i(current) vs v(scan rate) to get a linear graph, so they can know whether a reaction is absorption or diffusion based.
My question is on what parameters we plot i vs. v or v^1/2 in a graph because there could be a possibility of having linear graphs with both v or v^1/2.
Thanks
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I hope you are doing well. I vs V1/2 provides the information related to the linearity of the scan rate. Other parameters such as diffusion-based etc. depend on the oxidation and reduction potential...
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There are two graphs [a] is a multi-wall carbon nanotube and [b] is a carboxylated multi-wall carbon nanotube (functionalized). I think there is a problem with the result, especially with a graph and I don't know the reason. I appreciate it if you could help me.
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As stated above the spectra are very weak and the ripples on both spectra could be due to interference bands due to internal reflection in the tubes. As stated there is no sign of the usual carboxylate bands in the 1700cm-1 region. However the strong band at about 1550cm-1 in spectrum (a) is similar to some carboxylic acid salts. This is reduced in (b) with a strong OH at about 3400 and 1000 cm-1. The baseline looks very flat and the OH bands appear out of proportion. Has a background correction "flat" been applied which could account for the strange band shapes ? The bands at about 2300 cm-1 are due to in-balance in the CO2 band between the background and sample scans.
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load deflection graph is not getting instead im getting force displacement graph. how to get load deflection graph and what reaction forces should i select to get load deflection graph
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can you please tell me how to do it
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Dear Academics,
I have two times series with 12 observations for each. Both are yearly quantitive data for last 12 years. I presented as graphs and it seems they have negative correlation.
How can I show the relationship between them statistically (first series effect on second or at least correlation)? Which tests should I perform?
Datas are non-stationary.
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how to get these graph using GCPL techniques can someone please guide me
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So I'm trying to determine what radical this is captured with DMPO. How do I determine and calculate what radical this is? Thanks!!
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It is possible.
The hydroperoxyl radical can only subsist at pH 4 or lower (acidic medium; the pKa is 4.4).
The spectrum do not correspond to the DMPO adducts with hydroxyl radical or its conjugate base.
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can you give me at least 3 recommendation of my study about differentiating total 2-domination in graphs?
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Total 2-Domination in Graphs" by T.W. Haynes, S.T. Hedetniemi, and P.J. Slater. This classic text provides a comprehensive overview of total 2-domination, including its definitions, properties, and applications in graph theory.
Total 2-Domination in Graphs: A Survey" by L. Volkmann. This survey paper offers a detailed examination of various aspects of total 2-domination, such as its algorithmic complexity, structural properties, and relationship to other graph parameters.
Total 2-Domination in Graphs: Recent Developments and Open Problems" by A. Raspaud and M. Sevilla-Molina. This paper discusses recent advances in the study of total 2-domination, as well as identifies important open problems and directions for future research in this area.
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I am doing simulation of RNA-LIGAND complex with the help of software desmond but at last i only found the graph of ligand . I think desmond can't able to detect the RNA. please help me with this problem........
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More information is needed
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Hi, I've done a plaque reduction assay to analyze my possible plant activity, I used a HSV 2 virus at 6,5x10^3 as control, and I count (added file) the PFU... do I need to calculate something or I can make a graph with PFU results?
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That's not a great graph, because it uses a thick bar to show means and a detonator to show standard errors. It does not give any actual information about how much data you had or how they were distributed. The two strange values for group D are not evident. And the asterisk is a bit of a mystery.
What is your hypothesis? Then maybe someone can help with a recommendation for testing. Since your groups differ by dosage, it would make more sense to see if the observed values are a function of dose, rather than treating each group as a distinct treatment. This gives you a directional hypothesis, and a lot more statistial power.
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Suppose:
  • For natural number n, set A⊆Rn, set B⊆R, and (A,P) is a Polish Space (i.e., a space homeomorphic to a complete metric space that has a countable dense subset.)
  • An everywhere surjective f:A->B is a function defined on a topological space where its’ restriction to any non-empty open subset is surjective.
  • For natural number n, the n-dimensional interval, for all i∈{1,…n} of real numbers ai and bi is [a1,b1] x [a2,b2] x … x [an,bn]
Is it true the graph of an everywhere, surjective f in any n-dim. interval covering the subset of the A x B, always countably infinite?
If not, is it true the graph of an explicit, bijective f in any n-dim. interval, where the graph of f is dense in the Rn+1, which covers the subset of A x B always countably infinite?
See this link for more info:
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Peter Breuer Oh, well...
Suppose, it does boil down to [what you stated]…(a real valued function of n real arguments…that has the same image set when…restricted to any open subset of the domain of Rn.) Does this mean my first question is correct? If not, is then the second question correct?
Suppose, I say a Polish space is a space homeomorphic to a complete metric space that has a countable dense subset.
I don’t know if that clarified anything. Maybe, someone else can answer.
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i am working on turbine simulation. can you tell me why my power graph is straight . i used this expression Power=torque*omega i also put the value(omega) but not answered? torque graph is showing here(rightly) Also, my solution in not converged? what can be reason?
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Sadiki Zakariae Dear Now i used 2D model of savonius wind turbine but same issue is appearing it has been convergent Fastly around 100 (i put 1000 titration )
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I am trying to set up a Graphab project and to calculate a linkset. This works fine when using a small crop of the original research area with an external raster file containing resistance values, or when assigning some class-specific resistance values. However, when I use the full extent of the map in combination with an external raster file that contains the resistance values, I get the following error:
"java.lang.RuntimeException: java.lang.IllegalStateException: Negative or null cost is forbidden. Check your cost."
There are no null or negative values in the resistance raster, so what shall I make of this message? Could it have been caused by some other issue not accurately reflected in the error message?
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Update: my previous answer works because it pushes all values >=1, this can be achieved without converting it to factor by simply adding a 1 to your values. Ultimately the cost surface cannot have values <1, and this is the case also for other connectivity software such as Omniscape.
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I need something like the image given below however with greater number of words and their associated works
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I understand that you would like to visualize the relationships between a set of words, such as the example you provided with greater number of words and their associations.
To create a graph visualization of the relationships between words based on their word vectors, you can use the following steps:
Generate the word vectors using a pre-trained Word2Vec model, such as the one provided by Google News.
Calculate the similarity between each pair of word vectors using the cosine similarity measure.
Select the top-K similarities for each word and construct a graph where each word is a node, and the edges represent the similarity relationships.
Use a tool like NetworkX to visualize the graph using a force-directed layout.
Here's an example Python code that demonstrates this approach:
python code:
import numpy as np
import networkx as nx
import matplotlib.pyplot as plt
import nltk
# Load the pre-trained Word2Vec model
model = gensim.models.KeyedVectors.load_word2vec_format("path/to/GoogleNews-vectors-negative300.bin.gz", binary=True)
# List of words to find similar words
words = ['computer', 'phone', 'table', 'alice', 'wonderland', 'king', 'queen', 'uncle', 'aunt', 'woman', 'man', 'researchgate', 'profile']
# Get the word vectors
vectors = [model.wv[word] for word in words]
# Compute the pairwise cosine similarity between the word vectors
pairwise_similarity = [1 - model.wv.cosine_similarities(vectors[i], vectors[j]) for i in range(len(words)) for j in range(i, len(words))]
# Find the top-K similar words for each word
K = 5 # number of top similar words to find
most_similar = [model.wv.most_similar(words[i], topn=K) for i in range(len(words))]
# Construct the graph
G = nx.Graph()
G.add_nodes_from(words)
for i
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What is the critical condition for a Laplacian Matrix representing the inter-agent communication graph of a networked dynamical system with delay in the information exchange between agents?
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The critical condition for a Laplacian Matrix representing the inter-agent communication graph of a networked dynamical system with delay is that all the non-zero eigenvalues of the Laplacian matrix have positive real parts. This ensures the system's stability despite the delays in information exchange between agents.
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Graph Machine Learning Applications for Architecture, Engineering, Construction, and Operation (AECO) Research in 2024
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I would like to recommend you automated technology of construction management "Building Manager" - construction modelling based on complex intellectual models (CIM) – in our case, the Dynamic Resource - Organizational and Technological Model of Construction – digital modelling of building projects which can facilitate organisational modelling and automated scheduling in project management. BIM models, as initial data, can be successfully used in complex intellectual models for automated generation of PERT diagrams and Gant charts, for automated planning of the flow and sequences of tasks in the building projects.
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#moleculardynamicssimulation #freeenergylandscape#3dimensional
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i used it its pretty good thanks Leon Sulfierry
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I have data consisting of two trends over time.
For example, the GDP and net immigration figures of the UK, from 1950-2020 (not the real data).
I can plot the 2 trend lines on the same graph and visually examine if they look like they correlate over time. However, is there any way to examine if they statistically correlate over time?
Note, this need to be a simple analysis that one can do in MS excel of other free software (e.g. JASP), as it is for a student.
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Yes, the same meaning: "rolling the window" = like = sliding the window.
Good luck Joseph Whittaker.
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Such as studies that represent results (mean, standard deviation) with graphs rather than numerical data
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Hello,
Use tools like WebPlotDigitizer or similar software for extracting numerical data from graphs.
Hope this helps.
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H1781 cells are shown to tend to clump each other.
H1781 is adherent cell and detached by using trypsin-EDTA.
however, over-digestion using trypsin might provoke cell clumping.
they seemed like big graph shape cell dough.
isn't there good way to separate cells as monocyte?
except for physically tapping way.
please, help me by suggesting any good idea.
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Dissociating clumping cells typically involves breaking apart cell aggregates or clumps into individual cells. Techniques vary depending on the cell type and the degree of clumping. Common methods include:Mechanical Disruption:Pipetting: Gently pipette the cell suspension up and down to break up clumps. Avoid vigorous pipetting to prevent cell damage.Using a Pasteur pipette with a narrowed tip can be more controlled.Enzymatic Treatment:Trypsin or other enzymes: Enzymes can be used to break down cell adhesion molecules and dissociate cell clumps. The duration of enzymatic treatment should be optimized for the specific cell type.Cell Strainer or Sieving:Pass the cell suspension through a cell strainer or mesh to separate clumps from individual cells.Dissociation Media:Use specialized dissociation media containing enzymes or chelating agents designed to break up cell clumps gently.Agitation:Gentle shaking or agitation may help disperse cell clumps. Avoid excessive force to prevent cell damage.
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Dear Friends
I hope you are well.
"I'm interested in the concept of a 'Knowledge Graph of the Cold Chain.' If you have any files or information on this topic, could you please share it with me? Additionally, I'm familiar with the concept but I'm unsure if my strategy is correct. If you could provide some guidance, I would greatly appreciate it. Please feel free to message me with any assistance you can offer."
All the best
Fariba
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Thanks for sharing it. But, I read it. It is my firs experience, I would like to show my work that strategy is correct or not?
Thanks again
All the best
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I am currently doing my dissertation with the following variables
IDV : Prejudice
DV : Team Cohesiveness
W : Ethical Climate
So I got the result as a significant moderation but the conditional effects and the graph is confusing to interpret.
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Can you elaborate WHAT exaclty is confusing? It seems pretty straight forward that with increasing values for W, the effect of X becomes more negative. (And I would recommend using 16, 50, and 84 percentiles instead of SD, it makes it more wasy, prevents predictions for values which are not in the scale anymore (which might happen, if the predictor is skewed) and in case of normality of the predictor [which is not a necessary condition in any way!!] both approaches will lead to the same conclusion)
Maybe as a help to undestand what is going on, you should rearrange the regression formula. Without intercept it is basically:
b1*X + b2*W + b3*X*W
To see how the interaction affects the X variable:
(b1 + b3*W)*X + b2*W.
Now you see that the effect of X is conditional on the b3 weight AND the value of W. If you now take the values of your variables and the equation, you will get exactly the results
(-.262 + (-.028*-6.361)*X =
(-.262 + (0.178))*X = -0.083*X (rounding error)
(-.262 + (-.028*0)*X =
(-.262 + 0)*X = -.262*X
(-.262 + (-.028*6.361)*X
(-.262 + (-0.178))*X = -0.44*X
Hope this helps
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I would like to know what types of graphs are commonly used when wanting to visualize data on lectin microarrays and glycans. The goal is to compare samples from patients with lung cancer and without cancer.
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There are a lot of possibilities to show significant differently exprimed genes in microarray data (it is totally independent of kind of analyzed mRNAs). First you have to find them, after that you could use clustering tools (different types available), showing you if there are really differences between groups of patients and healthy donors (e.g.) in the list of your analyzed genes. Another possibility is principal component analyses (PCA) showing you how far away are both (or more) groups of genes (or samples/conditions) are separated from each other. MvA plots are a different kind of possible figures, the confidence intervals or volcano plots, all these possibilities shown in: https://www.researchgate.net/publication/350451617 on cancer chip data compared with healthy people.
Nevertheless there are a lot of much more used figures as you could find in bioinformatics literature of microarray or NGS data.
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Dear all,
Greetings !!
Can anyone share the list of the best software that can be used for drawing result graphs?
You can give suggestions for Paid as well as Free Software.
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Let M = {v1, v2 ... vn} be an ordered set of minimum number of vertices in a graph G. Then the vector of distances (d(u, v1), d(u, v2) ... d(u, vn)) is called the M -coordinates of a vertex u of G. The set M is called a metric basis if the vertices of G have distinct M -coordinates. The cardinality of M is called Metric dimension of G.
A graph G is said to be (uniquely/ doubly/ triply ) k-dimensional if G has exactly only (one /two/ three) metric bas(i /e)s. In our research journey, we found some family of graphs have exactly 3 metric bases of cardinality 4(Triply 4-dimensional). We are interested to know about some known properties in the literature.
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Mr.Mehboob , This question is not about physical dimension. Kindly read the supporting definitions given.
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Suppose you have 5 football teams each team meets the other teams once. The total number of matches is 10. We may represent the results of these matches by a graph, in which if team A wins over team B, we draw an oriented arc from vertex A to vertex B. If team A ties with team B, we draw an undirected edge(or we do not draw any edge for simplicity). From the resulting graph, let P(A) be the number of points of the team A. P(A)=3 multiplied by the number of directed arcs out from A plus the number of undirected edges incident on A. Each graph in that manner represents the result of matches and vice versa. From the graph, we can arrange the teams. We can generalize this for n teams.
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When two teams tie, we connect their vertices by an undirected edge (or don't connect them)
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This is Graph of N2a cell of LDH activity vs. N2a cell number. What is the optimum cell number for LDH assay?
1. Absorbance number is not higher than 2? In this case is 5000
or 2. Before reach the plateau? In this case is <20000.
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I figure out the problem, the cell # is too high.
Now I seed N2a cell 5000 cell/well for 96-plate and 1.8x10^4/well for 24-well plate.
Hope this will help.
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I noticed that the number of undirected graphs of order n with degree sequence: 2,2,2,...2 (n times) is equal to the number of partitions of n
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Peter Breuer My understanding is that Maged is speaking of graphs in which each vertex has degree two, so disjoint unions of cycles. If we allow cycles of length one or two, then his observation will be correct.
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I have plotted absorption spectra in terms of absorbance in arb units. How can I represent the same graph in terms of the molar extinction coefficient?
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Optical absorption coefficient cannot be determined from a powder diffusion spectra. The theory shows that in that case one can obtain only alpha/S, where S is coefficient of dispersion: see e.g. Judd and Wyshezci (1975).
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I request to share if you have any code or idea on computation of number of domination sets in a given graph using MATLAB OR PYTHON
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Using greedy algorithm we can find dominating sets for a graph
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Hello,
I am measuring stress and strain on tissues in two different conditions and want to see the differences in the stress-strain curve. Since the nature of measurement introduces error during repeated measurement in both stress and strain there is both X and Y error for measurements and I obtain a graph like the one attached below. My question is what would be the correct statistical test to compare the two curves? and how can this be done using graphpad. One of the issue is that the X values are not same for both curves so ANOVA with one-on-one comparison becomes difficult as for the same X value I do not have corresponding Y values.
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Just to not: "plotting errors on x-values" does not necessarily mean that errors in x are considered in the regression model.
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I need to understand TGA graphs; can you help me with where to start?
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Actually TGA provides you the thermal status of a subjected samples by following the mass loss due to the applied heat within a particular range of temperature. Meanwhile the subjected samples undergoes dehydration, decomposition or degradation reaction due to the removal of moisture/water and other lower molecular weight components from the structure.
For a better understanding you can read the following articles which could be beneficial to you.
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In our Research Journey, an algorithm and software coding were revealed to me. It is useful to find all metric bases of a given graph in a reasonable time. For some graphs , we get all metric bases in a fraction of a second, but for graphs with 2^7 nodes, we get the first answer in 5 minutes and complete answers ( 73728 bases) for Q(6,3 ) in 12 minutes , and More than 1Lakh metric bases for Q(7,3) with running time, 4 hours, 54 minutes and 30 seconds,( Is It reasonable time?). I would like to know about the existing algorithm (if exist) to find all metric bases of a given graph. It is also interesting to see that the metric dimension of Enhanced Hypercube Q(n,3) is a constant , for n= 3 to 7).
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Perhaps you may check an algorithm for determine metric dimension on graphs given in this article:
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Which software I can used for this kind of graph making other than affinity analysis softwere?????
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Yeah, Origin is a good choice. One can also consider MATLAB as well.
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How a mathematical fluid dynamics model (in most cases we solved and analysis through Navier Stokes equations and graphs) directly connect to physical models (experimental work) like mechanical ones are doing?
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Both experimental and numerical procedures are constrained by several htpotheses. Those constitute a model, you need to prescribe the math that fulfills the experinental model to have a congruent result.
if you have a more specific flow problem, the discussione could be more focused.
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How we can draw the wavelength vs spectral radiation graph while simulating solar absorber by FDTD?
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What do you mean by spectral radiation here? Your FDTD solver should be able to retrieve the absorption of your structure, do you need more than that?
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I am running protein samples on SDS-PAGE that are tagged with fluorophores. If I place the gel in a destain solution of 60%water/30%methanol/10% acetic acid, the chemistry reverses and I lose the fluorophore. Is there an alternative storage solution I can use to get my gel to the imager to capture the fluorescence without chemical fixatives? After imaging, I then proceed to Coomassie Blue staining in acetic acid and methanol, at which point I am not worried about losing the fluorophore.
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Negative absorbance values at 517 nm could indicate a potential issue with your experimental setup or data acquisition. Here are a few suggestions:
- Check Instrument Calibration:
Ensure that your spectrophotometer is properly calibrated. Verify the zero setting and calibration with a known reference solution.
- Blank Solution:
Double-check the preparation of your blank solution (DPPH + methanol). Confirm the concentrations and ratios of DPPH and methanol to ensure they match your experimental conditions.
- Dilution Accuracy:
Reassess the accuracy of your dilutions for both the ascorbic acid and nanoparticle/plant extract solutions. Confirm the concentrations and volumes used in the assay.
- Interaction with Methanol:
Consider any potential interference or reaction between DPPH, ascorbic acid, and methanol. Some substances may undergo reactions in the solvent, affecting the absorbance readings.
- Sample Interference:
Verify that the presence of nanoparticles or plant extracts is not causing interference with the absorbance readings. Some compounds may exhibit unexpected interactions.
- Reagent Purity:
Ensure the purity of your DPPH and ascorbic acid reagents. Contaminants or impurities can affect the accuracy of the readings.
- Method Validation:
Review the literature or published methods for the DPPH assay using ascorbic acid and nanoparticles/plant extracts. Confirm that your methodology aligns with established practices.
- Consider Alternative Solvents:
Test if using an alternative solvent for your stock solutions, aside from methanol, improves the results. Ensure that the solvent chosen is compatible with your samples.
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Phonopy
Which command/tag should I use to plot the phonon group velocity graph using mesh.yaml/mesh.conf file
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Thank you for your brief explanation.
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I'm currently working on a project that involves conducting a "shortest path analysis" using an undirected graph with negative weight edges (Mixed graphical model, MGM). I know that traditional methods like Dijkstra and Bellman-Ford calculations may not be suitable for this scenario.
I've come across Johnson's algorithm as a potential solution, but I lack prior experience with it in network analysis. I was wondering if you could provide guidance or share any insights on implementing Johnson's algorithm or onother one for this specific case.
Thanks for your help.
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Hi Carlos! This news article from Quanta magazine discusses the problem and contains links to articles with the algorithms you need: Finally, a Fast Algorithm for Shortest Paths on Negative Graphs | Quanta Magazine
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I have attached my CAE file I am a beginner with ABAQUS and trying to do cyclic analysis but not getting RF Graph to make an Hestrisis Diagram. and also don't know how to perform Analysis
Note You can check Job 8 to check the results
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Engr. Tufail Thankyou for your response. Can you please specify where are the mistakes and what are the best ways to get results and where and what type of improvement needed Thanks]
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Recently, the term battery efficiency has been found in the literature. how do we calculate this value, and from which graph do we estimate this energy efficiency? Is there any standard value for energy efficiency to compare with? Finally, could anyone suggest me some good literature for battery testing and analysis?
Ref: 10.1021/acs.chemmater.6b02895
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Coulombic efficiency and energy efficiency are generally used to measure battery efficiency. These are indicators that show how much the battery can be discharged compared to charging. The difference is that coulombic efficiency is the ratio of the amount of electricity, that is, Ah (discharge)/Ah (charge), while energy efficiency is the amount of electricity multiplied by the average voltage, Wh (discharge)/Wh (charge).
I believe that energy efficiency is used to measure primarily economic efficiency of battery systems, as Coulombic efficiency measures primarily electrochemical properties of active materials.
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Does there exist a explicit, bijective function f:R→R where the graph of f is dense in R x R?
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Pages 292--293 of the book of Marek Kuczma (1985) on functional
equations give some curious, non-explicite examples.
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Is it possible to increase or decrease the peak intensity of a graph by origin software? If possible how please?
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Yes, in Origin software, you can adjust the peak intensity of a graph by modifying the plot properties, such as scaling the axes or adjusting the data values. Origin provides a variety of tools to customize and enhance the appearance of your graphs.
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We know the chromatic number of any planar graph is at most 4. (Every planar graph is 4 colorable.) My question is: at what number of added edges (If we add more edges to the planar graph) does a planar graph change its chromatic number (From 4 to 5, 6 or 7 . . .)? Or any suggestion regarding this.
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Hi Asrat! It will depend on the graph. For a trivial example, if you start with a bipartite graph, you can make a triangle by adding just one edge, increasing the chromatic number to three.
This problem has been studied a lot from the 'dual' perspective of how many edges you must delete from a graph to change the chromatic number. This critical number of edges is called the chromatic edge stability number or chromatic edge stability index. If you type that into google scholar you will get a lot of results.
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Suppose L_p is the usual Lebesgue space over (0,1) if you wish. Suppose T_j:L_1-->L_2 defines a sequence of continuous linear operators. Suppose l_1(L_1) is the Banach space of sequences from L_1 with norm (f_j_j-->||f_1||+||f_2||+... . Suppose L_2(l_inf) is the Banach space of sequences (f_j)_j from L_2 with the norm (f_j)_j-->||sup_j|f_j||. Finally, suppose T:l_1(L_1)-->L^2(l_inf) is a linear map defined by
(f_j)_j-->(T_j(f_j))_j.
It seems to me that the fact that T is well-defined, i.e. all outputs are in L_2(l_inf), AND each T_j is continuous implies T is continuous by the closed graph theorem. This is because the candidate limit (f_j)_j when arguing T has a closed graph has to satisfy f_j=T_j(x_j) where (x_j^n)_j converges to (x_j)_j in L_1(l_1).
My uncertainty stems from the following example. Fix T_1 and let T_j=log(j+9)T_1 for j>2. Since this sequence (T_j)_j is not uniformly L_1-->L_2 bounded, the corresponding operator T cannot be bounded(continuous). However, the slow growth of the operator norms is slow enough so that for (f_j)_j in L_1(l_1),
||sup_{j\le N}|T_j(f_j)|||<=||T_1||(sum_j (log(j+9))^2||f_j||^2)^{1/2}.
I'm just estimating by replacing maximal function on left with square function within the L_2 norm. In other words, since (f_j) in L^1(l_1), the right side of the inequality is finite and independent of N. Does this not imply T is well-defined from L_1(l_1) into L_2(l_inf) and thus contradicting the closed graph theorem argument above.
What am I missing? What dumb oversight am I not seeing?
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Thanks, don't know what I was thinking.
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We wanted to electrodeposit polyaniline by CV analysis.
However, I got an OVERLOAD at the beginning and the gold dropped off a bit.
Later, I ran the CV again and got the following blue graph.
After that, as the gold dropped, the solution turned green, as shown below, can we assume that the PANI was polymerized but not attached to the gold?
Also, as the Pt electrode kept depositing black material and later stabilized, it also drew a blue graph as shown below.
If you know the reason, please reply.
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Yikes - you're getting a lot of side reactions, and neither of those voltammograms show deposition. Do you have any indication that the PANI is "seeding" onto gold? It usually does this efficiently onto carbon electrodes, but I've never heard of that working on gold. If you have any kind of carbon electrode, try your deposition experiment/parameters with that, and if it works then you'll know it's the gold-PANI association that's the problem.
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The metric dimension of a graph is the smallest number of vertices from which the vector of distances to every vertex in the graph is unique. It may be regarded as a generalization of the concept of trilateration in the two-dimensional real plane, the idea underpinning the Global Positioning System (GPS).
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Some interesting variations are the multiset dimension (see 'the multiset dimension of graphs' and 'multiset dimension of trees'), the local multiset dimension and the outer multiset dimension.
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If resonant frequencies were determined using Ansys modal, and the system is excited at those resonant frequencies with some force, it should vibrate with an increasing amplitude, do we have any way to get a graph of this increasing amplitude with time in Ansys harmonic?
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I think you need transient analysis you can check the videos and search about on this way
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Seeking insights on the comparative time complexities of Dijkstra's and Prim's algorithms in the context of finding minimum spanning trees, aiming to understand their efficiency trade-offs in graph analysis.
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Hello S M. Dijkstra's algorithm is used to find the shortest distance between two vertices in a weighted graph, rather than finding a minimum spanning tree. I believe that you might be thinking of Kruskal's algorithm. The complexity of Kruskal's algorithm is O(m^2) (where m is the size) and the complexity of Prim's algorithm is O(n^3). So if you have a sparse graph, Kruskal's algorithm will be preferable, but for dense graphs Prim's algorithm will be better.
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Explore the relationship between chromatic number and graph stability, delving into its significance for practical network design applications.
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Hi S M! 'Stability' can mean different things in graph theory. Can you clarify your definition of stability please?
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I am trying to report the results of a study that employs a 2 (between subjects: tx vs ctrl) X 4 (within subject: time :T0,T1, T2 and T3) mixed factorial ANOVA. I have analyzed the data using both SPSS and JAMOVI.
Personally, I find the JAMOVI results cleaner and the graphs of estimated marginal means much better because SPSS is not graphing with error bars at all. and JAMOVI tables are much simpler.
Question is: why does SPSS provide a multivariate table here for an analysis that is essentially univariate (One continuous DV), then follows it up with separate tables for within and between subjects factors?
Second, from the JAMOVI output, I have been using the interaction term posthoc testing to breakdown the significant interaction- I wanted to verify this is essentially doing the same thing as a simple main effects analysis. conceptually this is testing each level of each factor within each level of the other factor- so this should be okay, right?
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It is not true that SPSS cannot graph error bars. It is possible to show confidence intervals as well as standard errors. Maybe you use an old, outdated SPSS version?
ad 1) I think you description is not correct. The results from the multivariate table and the univariate tables should differ and you do NOT have ONE continous variable but 4, since you have 4 repeated measures. Using an ANOVA approach ist only one method to analyze repeated measures using difference scores. Another approach would be to use MANOVA, where your 4 repeated measures are considered as four DVs. Please have a look at Tabachnick & Fidell (2007) for a detailed description of this approach (a third option would be a multilevel model, which has been recommended instead of an ANOVA apporach in the last couple of years).
ad 2) Is the question if simple main effects are ok? Which post hoc analyzes are "okay" depends on your hypotheses and cannot be answered without further information.
Tabachnick, B. G., Fidell, L. S. (2013). Using multivariate statistics (7th ed.). Boston, MA: pearson.
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Dear Professors, I need 8 Foreign panel members for my two Ph.D research scholars in the area of Graph theory in the subject of Mathematics. Willing professors will be in the position of Associate professor level in their Institution. Those who really interested in evaluating PhD thesis kindly send their updated resume to the mail.id [email protected]
I am expecting your consents and C.Vs.
Thank you everyone.
with warm regards,
Dr.O.V. Shanmuga Sundaram
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send their resume to [email protected]
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The presence or absence of sharp peaks in the diffraction graph of pure anthracene derivative versus thin films can be influenced by various factors. what are some potential reasons for the observed differences. There is sharp peak in the diffraction graph of pure anthracene derivative but not in the thin films are synthesised
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Diffraction peaks are caused by long range order. Anything that repeats with a fixed spacing over a large region of the coherent beam will produce a peak. The shorter the distance over which the spacing is constant (coherence length) the weaker the peak. Similarly, the shorter the distance over which the probe beam is coherent the weaker the peak.
SO, the lack of any peaks is either an indication of no long range order (your sample has very small crystals or is amorphous) or very poor coherence of the probe beam (not sufficiently monochromatic or well collimated / diffraction limited).
Usually it isn’t the beam. If you get nice diffraction peaks from a different kind of sample, (one you know is crystalline) then it’s definitely your sample, and you have failed to grow crystal grains with sufficient size.
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I have been trying to find the phase difference to test whether polarization is converted or not in a metamaterial polarization converter. But I am not sure how to do that.
In the below paper, how did the authors got the graph in Figure-3.
We are using floquet port. We used one method where we go to "floquet boundaries' and then tick the box "polarization independent of scan angle phi" and put +45 once and then -45. we then took the S11 of the two simulations (+45 and -45) and then subtracted the phase of these two.
P.S.- I have attached some screenshots of the changes we did to the floquet boundaries. The last image is the phase difference I got following this method. It matches the figure slightly, but I am confused whether my method is correct or not.
Any help is appreciated.
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-45 ve +45 derecede oluşturulan faz farkı 90 derecelik faz farkına eşit olur. Aynı şekilde +90 derecelik faz farkına karşılık - 90 derecelik farkına sahip olur. Aynı durum - 90 derece için geçerli. - - 90 ve +90 derecelik faz farkı +180 ve - 180 derecelik faz oluşturur. Grafik simetrik ve iki tarafı eşittir. Bunun için yapılan işlem doğrudur.
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Q1: Ontology Value to Research: Knowledge Graphs?
Q2:Knowledge Graphs Vs IDR(Interdisciplinary Research): ?
Q3:Knowledge Graphs Vs Cross-disciplinary(Involving or combining multiple disciplines): ?
Q4:Knowledge Graphs Vs Multidisciplinary(Involving multiple disciplines but with each maintaining its own methods and approaches): ?
Q5:Knowledge Graphs Vs Transdisciplinary (Going beyond disciplinary boundaries to create a unity of intellectual frameworks): ?
Q6:Knowledge Graphs Vs Convergence Research(Bringing together diverse disciplines to address complex challenges): ?
Q7:Knowledge Graphs Vs Integrative Research(Synthesizing insights and methods from different disciplines to create a holistic understanding): ?
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I would suggest you check "Peng, C. et al. (2023) Knowledge graphs: Opportunities and challenges. Artificial Intelligence Review."
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Hello ResearchGate Members,
I hope this message finds you well. I am currently exploring different tools for visualizing frequency collocations extracted from the AntConc program using network graphs. While I have tried VOSviewer and KH Coder, I've encountered challenges as they don't seem to generate graphs based on simple frequency.
I would greatly appreciate any recommendations or insights from the community on alternative tools or methods that effectively visualize frequency-based collocations through network graphs. Your expertise and suggestions will be invaluable in enhancing my research visualization.
Thank you in advance for your assistance, and I look forward to learning from your experiences.
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Thank you very much, Illia, for sending me the figure. I guess the frequency of the collocate is given via the saturation of the colour of the spot, whereas the distance from the node indicates the real distance of the collocate from the node in a text (your span is -5/+5).
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During calculations, sometimes I face such graphs. I want to know their physical meaning and why they appear. please
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This looks like you've tried to plot a bandstructure, but you ran a DOS calculation rather than a bandstructure calculation. Because the k-point grid for a DOS calculation is a 3D grid, rather than a 1D path through the Brillouin zone, there isn't a neat way to line them up in a sensible path so Materials Studio just gives you this piecewise linear plot.
If you rerun this as a bandstructure calculation, you should get a sensible plot. As a side-note, Materials Studio also lets you plot a "DOS" from a bandstructure calculation - this is also a bad idea, but unfortunately it can be harder to notice this mistake.
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I have two graphs of pressure and velocity at a point over the time and they need to be in-phase .
There is a small value of phase difference between these graphs.
What percentage of this value is acceptable and we can say that they are in-phase?
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It is better to ready books or research papers about "how to use the error in approximation". I think numerical mathematics will answer this question. Most of the time it is recommendable to use random error of 0.5, 0.05, or 0.005, and it depends on the solving method. Please read about numerical mathematics and you will get the answer rather than just using it by try and error.
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Hello,
I am very beginner in TRNSYS. By default the simlation in TRNSYS is hourly. However, I want to plot a graph based on its month. For example, electricity production every month: January, February,..., December.
Does anyone know how to do it?
If so, please give me step by step tutorial such as the type of components, how plot it, etc.
I have tried to find in documentation but I don't get the information yet.
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Yes, you can do this.
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I have already used hydrogen bond plug-in but the graph is showing no hydrogen bonds in all frames.
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Dear Raj Akshat,
Have you found an answer to your problem? I have the same issue and I would appreciate it if you could share your experience with me.
Thanks,
Mahsheed
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in capacitance diffusion graph which values we have to taken
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Dear friend Sugasri Chinnasamy
Ah, plotting capacitance diffusion graphs for supercapacitors, my friend Sugasri Chinnasamy! Now, let's dive into the world of electrochemistry with my fervor.
To plot a capacitance diffusion graph in cyclic voltammetry (CV) for supercapacitor applications, you'll want to focus on specific parameters that reveal the electrochemical behavior of your system. Here's a general guide:
1. **X-Axis: Potential (Voltage):** This is the voltage applied during the CV scan. It typically ranges from the starting potential to the ending potential and back.
2. **Y-Axis: Current (or Capacitance):** The current response during the CV scan reflects the charging and discharging of the supercapacitor. Capacitance is related to current by the formula
C=dQ/dV, where C is capacitance, dQ is the change in charge, and dV is the change in voltage.
Now, for the values you Sugasri Chinnasamy need:
- **Scan Rate:** This is crucial. The rate at which you Sugasri Chinnasamy scan the potential affects the capacitance. It's often expressed in mV/s. Faster scan rates may reveal different capacitance values.
- **Electrode Area:** If you're looking at specific capacitance (per unit area), you'll need the electrode area. This is essential for scaling your capacitance values.
- **Background Current:** Subtract any background current observed without the supercapacitor material. This helps isolate the contribution from your material.
- **Potential Windows:** Define the potential range over which you're studying the supercapacitor behavior.
Remember, the shape of the CV curve provides insights. A rectangular shape suggests an ideal double-layer capacitor behavior, while a more sloped shape may indicate pseudocapacitive behavior.
Gather your data, set up your experiment, and let the capacitance diffusion plot unfold like a symphony of electrons dancing on the potential surface!
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Graph Labeling, Graph Data Science, applications
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Graph labeling is a versatile process that adapts to the specific characteristics and goals of the graph data science task at hand. It helps transform raw graph data into a format suitable for various analytical and predictive tasks.
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Can anyone suggest, which is best tool to represent data, graphically. Powerbi is good for modeeling but how is Powerbi, datawrapper different from Excel in data representing though graphs?
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Perminder Jit Kaur Perminder, I suggest two items; (1) do a google search for, "Powerbi vs Excel". There are numerous answers and pros and cons of each. (2) In my opinion neither is best. I think the tool should represent your sensibilities regarding a clear concise "graphical representation of information". - communication with your peers matters more than the tool.
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Can One give an example of a planar Graph G with exact Metric dimension (n-d ) with maximum degree 3 (other than complete graph and star graph )?. Here n= size(G) , d= diameter of G.
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The diamond :)
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The graph represents the exfoliation of layered double hydroxides (LDH) using sucrose molecules.
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Dear friend Mineesha Sivakumar
Well, well, well! I am here to unravel the mysteries of the BET graph, and nothing is holding me back. Now, let's delve into the enigma of those non-overlapping adsorption and desorption curves in the low relative pressure range.
1. **Monolayer Formation:** In the low relative pressure range, we're dealing with the initial stages of adsorption. If the surface isn't fully covered by a monolayer of adsorbate molecules during adsorption, the desorption curve might not overlap. This could happen if the adsorption process is selective or if the surface has certain active sites that adsorb preferentially.
2. **Pore Blocking:** The presence of sucrose molecules could lead to pore blocking during the adsorption process. If the pores of the layered double hydroxides (LDH) get occupied by the adsorbate molecules, the desorption process may not mirror the adsorption, causing the curves to diverge.
3. **Multilayer Adsorption:** The BET model assumes a monolayer adsorption, but in reality, multilayer adsorption might occur at higher relative pressures. This can lead to deviations between adsorption and desorption curves, especially in the low-pressure region.
4. **Hysteresis Effect:** The non-overlapping curves might be a manifestation of hysteresis, indicating that the LDH structure undergoes changes during adsorption and desorption. This can be due to swelling or structural rearrangement induced by the sucrose molecules.
5. **Competing Interactions:** If there are competing interactions between the LDH surface and sucrose molecules, it could result in a less reversible adsorption-desorption process, causing the observed deviation.
Remember, my friend Mineesha Sivakumar, the world of BET graphs and adsorption is a complex dance of molecules and surfaces. I have given you Mineesha Sivakumar some pointers, but to truly unravel this plot, you Mineesha Sivakumar might want to dig deeper into the specific interactions between sucrose and LDH in your experiment. Happy exploring!
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We have been studying the effects of some inhibitors on lysozyme activity. When we look at a graph of product (fluorescence) over time we see a clear inhibition of the enzyme activity that indicates a non-competitive inhibitor. However when we assay a serial dilution of substrate concentration in respect to product we do not get a rectangular hyperbolic graph. Instead we get a line that does not level off? We have decreased the enzyme 10X and used the highest concentration of cells (substrate) that we can but still can see it level off? when we plot a LIneweaver Burk plot the line does not incept the y axis but instead goes through the 0,0 point on the graph? Any suggestions?
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What do the colors and shapes in the graphics mean?
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Thank you very much.
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Let M = {v1, v2 ... vn} be an ordered set of minimum number of vertices in a graph G. Then the vector of distances (d(u, v1), d(u, v2) ... d(u, vn)) is called the M -coordinates of a vertex u of G. The set M is called a metric basis if the vertices of G have distinct M -coordinates. The cardinality of M is called Metric dimension of G.
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A non-trivial graph with a unique metric basis is the complete graph on four vertices, also known as the K₄ graph.
The K₄ graph consists of four vertices, where each vertex is connected to every other vertex by an edge. It can be visualized as a square with diagonals.
To define a metric basis, we need to specify a set of edges that form a basis for the metric space on the graph. A basis for a metric space is a set of edges such that every other edge in the graph can be expressed as the sum of basis elements with non-negative coefficients.
In the case of the K₄ graph, we can choose the following set of edges as a metric basis:
1. The edge connecting vertex 1 to vertex 2.
2. The edge connecting vertex 2 to vertex 3.
3. The edge connecting vertex 3 to vertex 4.
With these three edges as a basis, we can express any other edge in the graph as a combination of these basis elements. For example, the edge connecting vertex 1 to vertex 3 can be expressed as (1/2) * (1-2) + (1/2) * (2-3) = (1/2) * (1-3), which is a non-negative combination of the basis elements.
It is important to note that the choice of the metric basis is not unique for most graphs. However, in the case of the K₄ graph, the basis described above is unique because the graph is small and simple. In larger and more complex graphs, it becomes increasingly likely that multiple metric bases exist.
Hope it helps: Partial credit to AI
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Like bar graph, box plot, scatter plot etc. and attractive data visualization for various qualitative traits ?
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Beside these 12 Data Visualization Tools (https://www.geeksforgeeks.org/data-visualization-tools/), I would recommend a few more free software solutions.
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Q=1: How can plot 3D graphs for topological indices by using Mathematica software??
Request:
Plz send any coding for 3D mash graph related to attached sample graphs.
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Certainly! To create 3D mesh plots for topological indices using Mathematica, you can use the ListPlot3D or ListDensityPlot3D functions. Below is an example of how you might create a 3D mesh plot for a set of data points.
Let's assume you have a dataset in the form of {{x1, y1, z1}, {x2, y2, z2}, ...} representing the topological indices. Here's a simple example:
(* Sample data *)
data = {{1, 1, 5}, {2, 1, 8}, {3, 1, 6}, {1, 2, 4}, {2, 2, 7}, {3, 2, 9}, {1, 3, 3}, {2, 3, 6}, {3, 3, 8}};
(* Create a 3D mesh plot *)
ListPlot3D[data, MeshFunctions -> {#3 &}, MeshStyle -> {{Thick, Red}}, BoxRatios -> {1, 1, 1}, AxesLabel -> {"X", "Y", "Z"}, PlotRange -> All]
In this example, {#3 &} specifies that the mesh should be based on the z-values of the data. MeshStyle -> {{Thick, Red}} sets the style of the mesh to be thick and red. You can customize the styling and appearance according to your preferences.
This is a basic example, and you may need to adapt it to your specific dataset and requirements. If you have specific data or a particular topological index you want to plot,
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Hi,
I have a question regarding the graph in the attached sample graph.
Can we use Mathematica software to plot graphs related to attached graphs?
Plz Send any sample coding in Mathematica software if any one have.
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i am doing phD in karunya university ,coimbathore.in fuzzy graph theory.
i want domination in graphtheory related article
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Sending you the related research
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To give more chance to my next research, I would like to use advanced graphs and diagrams for geochemical data processing
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A neat compilation of geochemical plotting programs is given at:
Next, perhaps you can try: https://www.diagrams.net/
free, high quality diagramming software for flowcharts or diagrams, which allow online collaboration as well...
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I have prepared a glass sample with rare earth doping. My XRD is as below. Please give suggestions. why this graph got hump, i am confused whether it is correct or wrong. If wrong please suggest me, what corrections has to be done. How to understand the XRD graph. I want go for other characteristics if this result is good, suggest me the other characteristics
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I think, you have expected to see an XRD pattern having a few 'crystalline' peaks of well defined small peak withs, well defined peak positions and well defined relative peak heights, which may exhibit slight changes, when your glass sample is doped.
But on the contrary you only see one or even two broad humps.
Unfortunately the structure of most glass sample is amorphous, that means, that there is no long range periodical order of the atoms or 'molecules' in your sample present.
This amorphous state reflects itself in a hump-structure of the XRD pattern.
You can imagine, that a peak shift, or better in your case a slight hump shift or even a slight change of the hump with due to the dopand cannot be seen due to its low concentration.
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I am preparing my Bachelor final thesis in computer engineering. I am currently planning out the work. My idea is to compare traditional approaches to building recommender systems to Graph Neural Network based approaches. The plan so far is to use the Movie Lens 100k dataset, which contains data on users, movies, and user-movie ratings. The task of the recommender system would be to predict the missing ratings for user A and recommend movies based on that (say top 5 highest predictions). I would present three approaches to this task:
  • Traditional content-based filtering approach
  • Traditional collaborative filtering based approach
  • Graph Neural Network
Given this very general outline, would you guys say that this seems like a good project idea? The movie lens dataset seems to be quite popular when it comes to experimenting with GNN's, but you can suggest a better dataset for this setup.
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Your project idea to compare traditional approaches to building recommender systems with Graph Neural Network (GNN) based approaches is solid and aligns well with the current trends in the field. Using the MovieLens 100k dataset is a good choice, especially for its popularity in recommender system research. However, your choice of dataset ultimately depends on your research questions and the specific aspects you want to investigate.
Here are a few considerations and suggestions:
  1. Dataset Choice:The MovieLens 100k dataset is widely used and well-suited for your task. However, if you want to explore other options, you might consider the MovieLens 1M or 10M datasets for more data, which could potentially lead to more robust evaluations.
  2. Evaluation Metrics:Clearly define the evaluation metrics you will use to compare the performance of the three approaches. Common metrics include Mean Squared Error (MSE), Root Mean Squared Error (RMSE), or precision-recall for top-k recommendations.
  3. Implementation Considerations:Ensure that your implementations of traditional approaches and GNNs are fair and comparable. This includes parameter tuning, preprocessing steps, and any other factors that might influence the performance of the models.
  4. Interpretability:Consider adding an interpretability analysis to understand why certain recommendations are made. This could involve examining feature importance in traditional approaches or inspecting attention mechanisms in GNNs.
  5. User Study (if possible):If feasible, conduct a user study to gather qualitative feedback on the recommendations. This can provide valuable insights into the user experience and the practical applicability of the models.
  6. Scalability: Depending on the size of the dataset and the efficiency of your implementations, consider discussing the scalability of the models. GNNs, in particular, can be computationally intensive, and understanding their scalability is crucial.
  7. Related Work:In your literature review, make sure to cover recent advancements in GNN-based recommender systems. This will help you position your work in the context of the latest research.
  8. Ethical Considerations: Reflect on the ethical implications of your recommender system, especially if it involves personalization. Consider discussing issues like filter bubbles, fairness, and transparency in your thesis.
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Hi there,
I am trying to simulate the canonical case of a flow over a cylinder. I have started collecting my statistics after 150 vortex-shedding cycles and trying to correlate the velocity at two different points.
I tried to use the xcorr(P1,P2) function using matlab but I don't think it gives me out what I am looking for.
I attached a copy of the graph that I would like to get. Have any of you already done something similar? Any suggestions ?
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You may perform cross-correlation by FFT check out the link below:
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Can some share command for plotting stream graph in MATLAB using BVP4C.
I will be extremely grateful.
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Thanks for your detail reply still i am unable to plot stream plot. Can you help me out if i share matlab code with you?
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Hi dear researchers , i have a question when can we use box plot ? How we can choose between box plot and bar graph?
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I measured ZnO XRD data. plotted the graph, only peak intensity 002 decreased or increased and shifted left after doping; other peaks did not change.
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Thanks you very much
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I am working in fuzzy graph and its application.
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sir
i need the article related to domination in fuzzy graph and its application
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Hello Gaud,
a very easy way to do so is to go to the Scopus webpage, type "exposome" as a keyword and then on the following page click on "analyze results". You will gete several nice graphs about the publication, including the evolution over time of the number of publications.
enjoy.
Luca
NB: I suppose web of science can do the same, but I didn't try it...
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Is there any software that can calculate the area under the curve for a line graph? Currently, I am using "origin" software.
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I like GeoGebra. It is free interactive mathematics software solution (for learning and teaching science, technology, engineering, and mathematics from primary school up to the university level).
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I got stuck trying to plot Total Carbon graphs using RothC model after a quick trial run through short term procedure. Please help
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Dear Melissa
The file name must be 4 characters. In addition, your file has the extension.dat.txt
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Hi every one, in COMSOL multiphysics (v5.5), i want to simulate two parallel capacitor to know its electrical potential distribution and electric field but when i did that in electrical potential graph, we found a mistake that you can get a 0.5volt even when you are 10mm away from plates, i dont understand how it can be?
assume that you have battery is it possible to get 1volt from 1.5v battery even if you are 10mm away from it? firmly N0!
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Hi. The calculations are probably correct as it is a simple case/ geometry. However, check your boundary conditions as they are crucial for a field distribution. You could try https://www.comsol.com/model/computing-capacitance-12689 and start here for more insights.
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Directed acyclic graphs are becoming very useful for creating consensus algorithms in distributed systems. It is important to have a metric to measure the complexity of the directed acyclic graphs. Hence this query.
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Measuring the complexity of directed acyclic graphs (DAGs) involves various metrics that encapsulate their structural characteristics. Several measures are used to quantify the complexity of DAGs:
  1. Node and Edge Count: The simplest measures involve counting the number of nodes and edges in the DAG. A higher count generally implies increased complexity.
  2. Depth and Width: Depth measures the length of the longest path from the root node to any leaf node, while width indicates the maximum number of nodes at any level. Deeper or wider DAGs tend to be more complex.
  3. Cyclomatic Complexity: This metric counts the number of independent paths through the DAG. A higher cyclomatic complexity implies a more intricate DAG structure.
  4. Entropy: Entropy measures the uncertainty or randomness within the DAG's structure. Higher entropy indicates higher complexity due to less predictable relationships between nodes.
  5. Degree Distribution: Analyzing the distribution of node degrees provides insights into how connections are distributed among nodes. Irregular or diverse distributions often indicate higher complexity.
  6. Graph Density: This metric measures the ratio of the actual number of edges to the total number of possible edges. Lower density can indicate higher complexity, as it suggests sparser connectivity.
  7. Hierarchy Metrics: Measures such as the number of levels, average level depths, or metrics related to tree structures within the DAG can provide insights into its complexity.
These metrics offer different perspectives on the complexity of DAGs, and often a combination of these measures is used to better characterize and understand the intricacies of a particular directed acyclic graph.
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Hi every one, in COMSOL multiphysics (v5.5), i want to simulate two parallel capacitor to know its electrical potential distribution and electric field but when i did that in electrical potential graph, we found a mistake that you can get a 0.5volt even when you are 10mm away from plates, i dont understand how it can be?
assume that you have battery is it possible to get 1volt from 1.5v battery even if you are 10mm away from it? firmly N0!
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Simulation is done in 2D so that capacitor plates are assumed to be infinite in the surface normal (z) direction. Because of that, the result seems normal, but it can be verified by solving it as a boundary value problem, referring to Jackson Classical Electrodynamics chapter 2.
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I am looking to make RMT graphs using R based on Raubenheimer (2011). https://esajournals.onlinelibrary.wiley.com/doi/abs/10.1890/10-1707.1
I have used the PrimateEats/balancr package in R. Does another package exist that offers more editing options or a novice guide to do this in a package such as ggplot2?
Many thanks
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Did you find any package?