Science topic

# Freedom - Science topic

Freedom is the rights of individuals to act and make decisions without external constraints.

Questions related to Freedom

True imperfect market theory suggest that imperfect markets do not exist when there is both market equality and freedom at the same time, which raises the question:

**Is a market where there is only economic freedom a true perfect economic market?**Think about it, what do you think?

If we use the solid elements to model the concrete slab, studs and shell element to model the beam, what would be happen to degree of rotations in the steel beam at the following interactions.
solid slab and and shell beam - surface to surface interaction
solid stud and shell beam - tie constraint

Will these interactions which doesn't take the all degree of freedom in the beam into account might lead in to imprecise results? please explain

What is the importance of degree of freedom in a research? Looking forward to your valuable feedback.

Unlike shell elements, solid elements have three degrees of freedom. So how can I get the values of moments after I run the model/analysis on ANSYS / ABAQUS ?

Greetings to all.

I am trying to perform a simple "mass diffusion analysis " on Abaqus CAE. But while computing job, getting an error saying :-

"Only degrees of freedom 11 and above can be active in the model for this procedure. Check the procedure and element types used in this model."

My model is:-

"Shell type" polymer film, with isotropic diffusivity properties, subjected to "surface concentration flux".

How, can I solve this error and carry out this finite element analysis.

My account at Twitter has been suspended because I shared official US Government information, posted by another user that I found when searching on a topic.

I was not given the option of hiding or even deleting the item, which showed a case reported to VAERS of a young child who died during a COVID19 vaccine trial.

The record contained clinical information that suggests it was lodged by a medical professional.

I would be interested to hear from other researchers who have had their social media accounts locked, suspended or terminated.

There is an example in Abaqus documentation to explain the active DOFs at nodes of User Element, which is totally different from the general order. Here is the example:

*For example, consider a 3-node beam that has degrees of freedom 1, 2, and 6 at nodes 1 and 3 and degrees of freedom 1 and 2 at node 2 (middle node). To order degrees of freedom 1 first, followed by 2, followed by 6, the following input could be used:*- USER ELEMENT
- 1
- 1, 2
- 1, 6
- 2,
- 3, 6

As I understand, node 1 has DOFs of 1,2,6, node 2 has DOFs of 2, and node 3 has DOFs of 6.

I can't understand how they arrange the DOFs at nodes. Could anyone help explain it?

When it comes to symmetry, Gaussian 16 is strange. It always converts the molecule's high symmetry into a low symmetric system, increasing the number of degrees of freedom. How to ensure that the symmetry is preserved and that the global minima are obtained.

In my situation, the symmetry in the B12 cluster shifts from D5h to Cs.

hi everyone

i saw in paper that finite element analysis of clutch disc(sliding and heat generation) is modeled in two‐dimensional axisymmetric in abaqus.

to do this one of the parts should rotate in around z(since there should be a rotational movement between parts to cause a friction and duo to that heat generation). but i cant find a way to that because there is only three degree of freedom is avaible in load section of abaqus. the pic is uploaded is from those papers.

is there a way to rotate parts around z direction in two‐dimensional axisymmetrics like this?

Hi!

I am trying to understand how personality traits change in adolescents over time (2 measurement occasions with the same individuals). I am using linear mixed models in SPSS for that purpose. I have "subjects" in "subjects" in the first block, "extraversion" as a DV, and "time" as a covariate in the second block (time could be a factor as well but I read that it might be better to put it in the covariate block actually). For fixed effects, I choose time as this is my main interest.

My question is if I should put "time" also in the first block under "repeated".

The analysis is very limited due to the fact that there are only 2 measurement occasions, so I cannot lose many degrees of freedom. If I do not add time in the repeated block, I can still add a random intercept and slope, but if I have to add time also under repeated, then I hit easily the iteration warning. Furthermore, I could add "sex" as a covariate, but to make all of these decisions, I first need to know if, for this particular design, where I only have time as a predictor, I need to have it in both blocks (repeated measures & covariate)?

I think that I do need to add it in both boxes. In that scenario I am not able to add any random effects due to iteration, but I can still add covariate of sex and interaction of sex and time. Please let me know if this is correct!

Thanks a lot!

Best wishes

Michaela

Hi, I am running a logit regression in Stata. I do not see standard errors and p values in some regressors (for a few models) and in all regressors ( in some other regression models).

Pseudo R square is 1 in the models where SE and p value corresponding to no regressor is reported by the Stata.

I understand that this is happening due to either the problem of separation (quasi or full) or reduced degrees of freedom due to inclusion of higher number of regressors (sort of k>n).

Details for dataset are as follow:

--> Model includes a regressor in the level form as well as the square term (quadratic function).

--> In addition, the model includes 9 control variables plus industry and year controls.

-> Industry includes 34 unique industries in form of 2 digit industry codes.

--> Year control includes 11 unique years. Cross-sectional data is pooled across those 11 years.

If I remove industry effect controls the results become inconsistent in the models. Somewhere these give opposite signs and in some models these become insignificant.

I would be grateful your kind suggestions.

Thanks you!

There are a limited number of countries in the world (about 200) they are so different in my understanding most samples would not be representative. And due to the limited number many times, it is possible to collect data about all countries. So can we infere with this data? Say I am doing research about freedom of press form time 2010-2020. When I analyse the data I can in my understanding only give conclutions about this time span and the countries examined and not about the future, the past or countries that where not analysed. And technically if I have data from all countries I have a population and do not need any probability at all.

Its easy to draw a column and release the degree of freedom at joints such that the column can hold gravity load but no moment. Similarly, I want do this for columns. Please advise which stiffness modifiers I will need to reduce for a shell element (wall) such that it is only resisting gravity load but not shear?

I have a lot of walls in my model. However, I want only some of the walls to resist shear (Earthquake) and all to be active to uphold gravity loads (dead & live).

In, one of my manuscripts, i have mentioned [F (4, 19) = 119.3, P < 0.001]. The reviewer asked 'What do F values represent (numbers in parenthesis)?. Here 4 indicates the number of groups, i.e 5, 19 indicates the total sample size 20-1=19, 119.3 indicates the degrees of freedom. Is there any wrong with the representation of F?

Hello,

My name is

**Mehide Hassan Ishaan**. I'm a student of "**Business Administration**". I wanna do research about "**To complete freedom of choosing own courses by students in College and University level**". I hope, it will be an interesting topic for all of us to observe in today's educational system. Glad to know that topic and expect more getting interest and comments from all of you.Thank you, "

*Everyone"*.Hi!

I was hoping someone could advise me as to whether the Kruskal–Wallis test by ranks produces error degrees of freedom? I have been asked for these by a reviewer but I am not sure they are associated with this test. Thanks in advance!

I want to know how to increase degrees of freedom in when testing moderation in SPSS AMOS and how to increase distinct sample moments.

I wanna to execute a research on' freedom of speech in social media in Bangladesh during covid-19.'

In a field experiment if there is possibility for both designs factorial RBD and Split plot design, and both qualifies as per degrees of freedom, then what design should be choose and why?

I have question regarding to 1d cantilever beam problem which is divided to five elements.

I want to reduce the degree of freedom for each node to 1(just keep uy)instead of 6.

I added fixed support in the first node and applied displacement on each other nodes( make it freely translate in y direction)

But it still gives me results for 6 dof for each node.

My goal is to get only 5×5 MK matrices but it gave me 30*30.

Anyone knows how to fix this problem?

Need Help!!!

Suppose, I have 4 questions regarding women's freedom of movement (Person who usually decides on go shopping, Person who usually decides on going to a health center or hospital alone, Person who usually decides on visits to your family or relatives, Person who usually decides on going to an outside town) and each question has 4 response categories like (0=not at all, 1= with husband, 2=with other,3=alone). Now I need to create a single variable named Women's mobility from that 4 questions. My question is can I combine all four question responses, that is in different columns into one column to create a single variable named Women's mobility? That is just merging 4 different response columns into one column by adding all columns as a row? For example, Charles is one respondent who answers 4 questions so 4 different columns now I make a single column by row-wise adding Charles's responses.

Please tell me whether it is the correct way to develop a new variable, rather than a mean score....

I have been tasked with designing a 4 (maybe 5) degree of freedom of freedom robotic arm that will be installed in the back of a van. Being in a van, its of importance for it to be as lightweight as possible while drawing as little energy as possible. Does anyone have any experience with this and can pass some ideas? Any sources for designs maybe?

I'm investigating the effect of economic freedom on health outcomes in Sub-saharan Africa.
I use panel data which N=37 and T= 19. When I tape xtset idc and year, Stata told me it's strongly balanced.
I would like to ask you if I can use the lsdvc estimator method? Or is there another estimator than GMM or 2SLS, because I've use it before

when I try to integrate the ACM model into aspen plus the following message appears " The block is not square. Degrees of Freedom (DOF) is -1 in the Parameters sheet. The block is under-specified when DOF is positive and over-specified when DOF is negative " how I can solve this problem?

we have this situation that we can't figure out from equations of articles and papers that how many degrees of freedom does a robot such as 3RRR Robot and other one have .

Do you know any special sources to learn ... ?

Can anyone explain why we use KMO and can we accept the value if the estimated value is more than 0.89 and what is the role of degree of freedom?

Hi,
When I am trying to run a model in ABAQUS Explicit, I get the following error message:
"Node 50000 has zero mass but not all spatial degrees of freedom are fully constrained at this node. Please assign a physically reasonable mass to this node."
But how do I do that? I haven't been able to find how to assign a mass to a dummy node.

Dear Ladies and Gentlemen,

I am a young PhD student who has just started the second year of the 4-year PhD programme. I am a political scientist specializing in British colonial political history, mainly South Africa and Ireland.

Some time ago, I finished writing a draft of my article on the question of liberty in the British Commonwealth, where the Irish Free State was a case study. The paper argues that understanding liberty as non-interference (Berlin, JS Mill and Bentham) was a foundation of the British policy towards its Dominions. It made the Commonwealth look more like a British colonial club, which was serving the interest of the Crown, and not a confederation of freely associated members (like the EU). Another argument is that Dominions, on the other hand, were subconsciously standing on the Republican understanding of liberty (Pettit, Mill, Harrington). The research uses Ireland to illustrate the abyss between the two concepts. It shows that the passionate Irish antagonism towards the Commonwealth was, to some extent, a result of that polarization of the viewpoints.

My question is the following. One of the respected reviewers has given me a comment that I must precisely explain how the two systems with their outlook on liberty apply to the question of collective freedom, the freedom of states, and not individuals. Thus, could you please help me with that? I felt that such an issue would pop up but was postponing its resolution until the comments arrived. How may I explain the application of the two outlooks to the freedom of the states? When does an individual transform into a collective? Is it possible to see a state as an equivalent of a living organism nowadays (IMHO, it is such an outdated and controversial concept that I would not dare following it to justify my logic)?

PS I was lucky to get comments from Skinner himself; however, I would love to hear as many thoughts as possible.

Thank you for any comments and recommendations.

Warm regards :)

As a result of communication with the WG participants, I came to the conclusion:

The lack of direct contact, complete freedom of expression leads to the fact that very often participants begin to humiliate, insult those who do not agree with their point of view.

Many adhere to a simple philosophy: there may be many opinions, ideas and guesses, but the correct one is only mine !!!

What is your experience and what is your impression of the WG correspondence?

Hi,

I get an error saying that my model is not sufficiently constrained when I connect solid element having 3 degrees of freedom to a shell / beam element having 6 degrees of freedom.

Is there a way elements with different degree of freedom can be connected in ANSYS APDL?

A rigid link or something?

Many papers suggest having a minimum error degree of freedom of 12. When a new crop variety is evaluated for agronomic performance with a local check or control, number of replications needed to generate a degree of freedom value of 12 is 13. That is, number of treatments (n-1) X number of replications (r-1), which is (2-1)X(13-1). I maintain this minimum degree of freedom for experiments with three or more treatment, however I not sure in the case of a paired field experiment. I would be grateful for your support and suggestions.

My co-author and I are working on a paper using the Economic Freedom of the World and 19 countries (sample cannot be increased because it is focused on a specific Region). The number of years is 19, then our sample is relatively short. We are trying to design a "non-orthodoxal experimental review", and apply diff-in-diff, but: 1) we do not have a specific treatment year, countries can be treated or not treated during all the period sample (treatment is if economic freedom score decreased, then country 1 can be treated in year 3, 4, 8, 10 (if its economic freedom score decreased those years) and not-treated in the other years that its economic freedom score did not decrease); 2) we are using an interaction model, my two interaction terms are treatment (1 if decreased the score of economic freedom, 0 otherwise), and intensity (the % variation of the economic freedom score), and other controls. We have presented in some seminars and conferences the research progress and early results of this paper but suggestions just focus on the "size of the sample", which we know could be a caveat but as I said the research intention is just the Region, the early results are significant and show the expected signs. We have not received suggestions on our "non-orthodoxal experimental review" (different treatment years, countries that can be treated or not in different years, our interaction model specification, etc...) My specific question is: Does anybody could give us some insights or suggestions on the methodology and how to respond convincingly that increasing the sample size is not an option for this research.

I imploted a script for calculating the acceleration of a single degree of freedom system for a certain dumping=0.1 and frequency= 2, and now I want to do the same thing considering uncertainty in dumping and frequency using fuzzy membership for both (dumping and dumping) and get acceleration.

anyone can help me?

A particle in a three dimensional volume has three degrees of freedom. So degrees of freedom are bestowed by dimension.

If dimension is fundamental, then how does space time scale? Does it scale like 4 dimensions, or does it scale like 4 degrees of freedom?

Time is not a dimension like the 3 dimensions of a volume, instead moving each point in a volume along a time line. If a 4 tuple qualifies as having 4 degrees of freedom but can only very loosely be described as having 4 dimensions, then would that make degrees of freedom more fundamental than dimension.

If space time is related to cosmogenesis, and energy propelled the universe into existence, then would dimension be a physical aspect of the universe consequent on 4 degrees of freedom?

Which came first physically: dimension or degrees of freedom?

Dear professors,

I am looking for a global database for any of the aspects of the quality of the institutions with yearly data since 1995 or earlier. I need it to be freely accessible. I know about the Corruption Perception Index from Transparency international and the Freedom of Press from the Freedom House.

Very much thank you in advance!

Hello,

I am currently reporting the results of my regression models. I can't find which degrees of freedom to report for the t-statistic.

Is it the residual df (203 in the example) or the total df (206 in the example)?

Thanks in advance!

There are currents of thought that points out that the Government should not take care of social aspects, for claiming that things naturally settle. On the other hand, there are ways of thinking that the Government should focus on the social, and sometimes end up creating so many tools of "aid" that stifle the freedom to do business. What could be a fair approach?

what is the degree of freedom on liquidus and solidus line in a binary phase diagram? not above liquidus where we have melt or below it where we have melt+solid. exactly on the line

Hi all,

I am looking at the impact of freedom in a country using the data from the freedom house index on socioeconomic development during COVID-19. In my study, I am using data from 171 countries.

I have created an index using geometric mean including variables such as water and sanitation, GDP, Healthcare quality, quality of education, unemployment rate, and Gini index for socioeconomic development. I have also created a Covid-Index using a geometric mean of total deaths per million and the stringency index.

My regression is: Socioeconomic development index = covid index + freedom score

I have run all the regression tests and all of them are statistically significant, and done tests for all the OLS assumptions (also passing them all).

My r-squared is 0.1442, how do I interpret this?

Thank you!

there are several methods for estimation of structural dynamic to predict the behaviour of the structure in motion. i am looking for a valid technique to analyze the movement of a bridge with single degree of freedom. i think most of the impact of the movement will be observed from the first mode shape of the structure when it subjected to any movement. i new in this research and want to explore this topic. if anyone can provide me some material regarding this topic i will be thankfull

I conducted a ML estimation in LISREL with Sattora-Bentler adjustment. Now I have multiple chi-square values (C1, C2_NT, C2_NNT, C3, C4). As much as I understand, the C3 is the mean-adjusted S-B chi-square and C4 is the mean- and variance-adjusted S-B chi-square. Now I am not sure based on which chi-sqaure were the other fit indices (CFI, RMSEA etc.) calculated and which ones I should report?

Here is the output:

Degrees of Freedom for (C1)-(C3),C(5) 4

Maximum Likelihood Ratio Chi-Square (C1) 15.006 (P = 0.0047)

Browne's (1984) ADF Chi-Square (C2_NT) 14.798 (P = 0.0051)

Browne's (1984) ADF Chi-Square (C2_NNT) 13.532 (P = 0.0089)

Satorra-Bentler (1988) Scaled Chi-Square (C3) 13.590 (P = 0.0087)

Satorra-Bentler (1988) Adjusted Chi-Square (C4) 13.366 (P = 0.0091)

Degrees of Freedom for C4 3.934

Chi-Square Scaled and Shifted (C5) 13.511 (P = 0.0090)

P-Value of C1 under Non-Normality = 0.0093

Estimated Non-centrality Parameter (NCP) 11.006

90 Percent Confidence Interval for NCP (2.699 ; 26.853)

Minimum Fit Function Value 0.0280

Population Discrepancy Function Value (F0) 0.0206

90 Percent Confidence Interval for F0 (0.00504 ; 0.0502)

Root Mean Square Error of Approximation (RMSEA) 0.0717

90 Percent Confidence Interval for RMSEA (0.0355 ; 0.112)

P-Value for Test of Close Fit (RMSEA < 0.05) 0.145

Expected Cross-Validation Index (ECVI) 0.148

90 Percent Confidence Interval for ECVI (0.132 ; 0.177)

ECVI for Saturated Model 0.135

ECVI for Independence Model 2.019

Chi-Square for Independence Model (28 df) 1064.176

Normed Fit Index (NFI) 0.987

Non-Normed Fit Index (NNFI) 0.935

Parsimony Normed Fit Index (PNFI) 0.141

Comparative Fit Index (CFI) 0.991

Incremental Fit Index (IFI) 0.991

Relative Fit Index (RFI) 0.911

Critical N (CN) 522.675

Root Mean Square Residual (RMR) 0.0191

Standardized RMR 0.0235

Goodness of Fit Index (GFI) 0.993

Adjusted Goodness of Fit Index (AGFI) 0.938

Parsimony Goodness of Fit Index (PGFI) 0.110

I am trying to carry out a study in which in the first step the cylindrical part only moves in the Y axis (for which I apply a BC limiting U1, U3, UR1, UR2 and UR3 = 0 and a pressure on the upper face of that part which cause its movement), however when in the next step I want the part to stay in the position in which it ended in the previous step (that is, it does not return to its initial position) I cannot do it.

I have tried to limit the 6 degrees of freedom in that 2nd step with a BC, but that causes that even in the 1st step there is no movement.

Would someone know how to do it?

I attach images and a video for a better understanding

Thanks in advance

*The step 1 only creates it to generate a heat load*

The nature of the social rights are always different to the other freedom ?

When social rights are contained in Constitution is it possible to justify this different approach ?

Are social rights considered only of the rights that cost or of the rights that impose a service?

Hello,

I am trying to show if there is any relationship between the different variables (weight, age, risk score) and freedom of re-intervention after a stent placement. Freedom of reinterevntion is a time depending value, so the more I think about it I think I should use cox's regression model. But on the other hand I am thinking weight/age/risk score and freedom of re-intervention are both continuous values so if I want to show a correlation between the two I should use the pearson/spearman? What do you think? Also if I am reporting the cox model, should I just report the hazard values and the p-values or may be more?

Thank you in Advance

Hi everybody

I have written following stepwise-MLR code in python for selecting informative independent variables:

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

def Stepwise_MLR(Xtrain,Ytrain):

import numpy as np

DIM_train=np.shape(Xtrain)

Rows_train=DIM_train[0]

Columns_train=DIM_train[1]

Ones_train=np.ones((Rows_train,1))

A=np.hstack((Ytrain,Xtrain))

B=np.corrcoef(A,rowvar=False)

CC=B[1:Columns_train+1,0].reshape(Columns_train,1)

index_R_max=np.argmax(CC) # the index of the variable with the largest r

var_sel=np.array(index_R_max).reshape(1,1) # index set of variables selected at present

K_selected=1 # Number of variables selected at present

var_available=np.setdiff1d(np.arange(Columns_train),index_R_max).reshape((Columns_train-1),1) # index set of variables still available for selection

K_available=Columns_train-1 # Number of variables still available for selection

# Main routine with entry and exit tests

# The flag_continue variable will be set to zero if no more variables can be either added to or removed from the model

flag_continue=1

yc=Ytrain-(np.mean(Ytrain)*Ones_train)

SS_about_mean=yc.T@yc # Sum of squares about the mean

while flag_continue == 1:

# Entry phase

# 1 - Before adding the candidate variable

Xbefore=np.hstack((Ones_train,Xtrain[:,var_sel].reshape(Rows_train,var_sel.size)))

b=np.linalg.inv(np.transpose(Xbefore)@Xbefore)@np.transpose(Xbefore)@Ytrain

yhat=Xbefore@b

# Evaluation of sum of squares due to regression

yhat_c=yhat-(np.mean(Ytrain)*Ones_train)

SSreg_before=yhat_c.T@yhat_c

# 2 - Testing the inclusion of each candidate variable

F=np.zeros((1,K_available))

# Degrees of freedom for estimation of the pure error variance in the augmented models

dof=Rows_train-(K_selected+1)-1

for index in range (0,K_available):

# Index of the candidate variable to be included

var_included=var_available[[index]]

Xafter=np.hstack((Xbefore, Xtrain[:,var_included].reshape(Rows_train,var_included.size)))

b=np.linalg.inv(np.transpose(Xafter)@Xafter)@np.transpose(Xafter)@Ytrain

yhat = Xafter@b

yhat_c=yhat-(np.mean(Ytrain)*Ones_train)

SSreg_after=yhat_c.T@yhat_c

# Estimate of pure error variance

RSS=SS_about_mean - SSreg_after

variance_hat = RSS/dof

F[0,index]=(SSreg_after - SSreg_before)/variance_hat

Fmax=np.max(F)

index_Fmax=np.argmax(F)

import scipy

from scipy import stats

Fcrit=scipy.stats.f.ppf((1-0.5), 1, dof)

if Fmax > Fcrit: # The variable with the largest F-value is added

var_sel=np.hstack((var_sel,var_available[index_Fmax].reshape(1,1)))

var_available=np.setdiff1d(np.arange(Columns_train),var_sel)

K_selected=K_selected+1

K_available=K_available-1

flag_entry=1 # Indicates that a variable has been added to the model

else:

flag_entry=0 # Indicates that no variable has been added to the model

# End of entry phase

# Exit phase

# 1 - Before removing a candidate variable

Xbefore=np.hstack((Ones_train,Xtrain[:,var_sel].reshape(Rows_train,var_sel.size)))

b=np.linalg.inv(np.transpose(Xbefore)@Xbefore)@np.transpose(Xbefore)@Ytrain

yhat=Xbefore@b

yhat_c=yhat-(np.mean(Ytrain)*Ones_train)

SSreg_before=yhat_c.T@yhat_c

# Estimate of pure error variance

RSS = SS_about_mean - SSreg_before

dof = Rows_train - K_selected - 1

variance_hat = RSS/dof

# 2 - Testing the removal of each candidate variable

F=np.zeros((1,K_selected))

for index in range (0,K_selected):

var_excluded = var_sel[0,index] # Index of the candidate variable to be excluded

# Index set of the predictor variables after excluding the variable under test

var_reduced = np.setdiff1d(var_sel,var_excluded)

Xbefore=np.hstack((Ones_train,Xtrain[:,var_reduced].reshape(Rows_train,var_reduced.size)))

b=np.linalg.inv(np.transpose(Xafter)@Xafter)@np.transpose(Xafter)@Ytrain

yhat = Xafter@b

yhat_c=yhat-(np.mean(Ytrain)*Ones_train)

SSreg_after=yhat_c.T@yhat_c

F[0,index] = (SSreg_before - SSreg_after)/variance_hat

Fmin=np.min(F)

index_Fmin=np.argmin(F)

Fcrit=scipy.stats.f.ppf((1-0.5), 1, dof)

if Fmin<Fcrit: # The variable with the smallest F-value is removed

# Index of the candidate variable to be excluded

var_excluded = var_sel[0,index_Fmin]

var_reduced = np.setdiff1d(var_sel,var_excluded)

var_available=np.hstack((var_available,var_excluded))

K_selected = K_selected - 1

K_available = K_available + 1

flag_exit = 1 # Indicates that a variable has been removed from the model

else:

flag_exit = 0 # Indicates that no variable has been removed from the model

# End of exit phase

flag_continue = max(flag_entry,flag_exit)

return (var_sel)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

But when I run it, I get following error:

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

var_sel=Stepwise_MLR(Xtrain,Ytrain)

Traceback (most recent call last):

File "<ipython-input-32-2ebd5729722f>", line 1, in <module>

var_sel=Stepwise_MLR(Xtrain,Ytrain)

File "C:\Users\B\Documents\Python Scripts\Python scripts_Sepehri\MLR\Stepwise_MLR.py", line 48, in Stepwise_MLR

b=np.linalg.inv(np.transpose(Xafter)@Xafter)@np.transpose(Xafter)@Ytrain

File "<__array_function__ internals>", line 5, in inv

File "c:\python38-32\lib\site-packages\numpy\linalg\linalg.py", line 545, in inv

ainv = _umath_linalg.inv(a, signature=signature, extobj=extobj)

File "c:\python38-32\lib\site-packages\numpy\linalg\linalg.py", line 88, in _raise_linalgerror_singular

raise LinAlgError("Singular matrix")

LinAlgError: Singular matrix

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

Why do I get this error?

** Attached files are written python code and used data.

Thank you so much

As I understand, with a large sample size chi square presents almost always statistical significance, so that we should not use this fit index to base on our acceptance/rejection decisions. What about chi square to degrees of freedom ratio ( χ2/df )? Are there circumstances where its use is advisable and circumstances where it is not?

Please, do not hesitate to suggest me very technical literature on this. I am curious about it and want to learn.

Working on a theory of paradigm shift and flips that is linked to equality and freedom it is possible to see clearly the structure of markets, including deep social markets and red socialism/communism based markets….

This understanding helps us see the options available to markets in terms of flips or shifts when under specific sustainability gap pressures, and it allows us to see which option they would exercise if they have a choice before paradigm death/collapse like the one we saw in 1991 related to the fall of Karl Marx's world/Red socialism.

From this angle, knowing the difference between different types of markets, especially close ones, is very relevant.

Looking at the deep social markets and red socialism/communism based markets, raises the question, can you see what was or is the difference between deep social markets and red socialism/communism based markets?

If you think you can see it please share it or describe it so we can exchange ideas.

Do you think of it as a part of life, as a disease without a cure, as a way of immortalization, as a way of transformation, as a way to freedom..or something else. Is it good or bad? We all know that it is the real truth of life but why we always fear to talk about it.

My major objective is to find if one data set is closer to another. With ten data sets I want to know which one are making clusters or can say have less distance with each other. I have already tried correspondence analysis, however it is not useful for factors having degree of freedom less than three. Any lead would be highly appreciated

Hi all,

I have been wracking my brain and searching the literature for answers, but yet none seem clear to me so I feel I must ask. Are "fit statistics (e.g., RMSEA, TLI, CFI, etc..) important or even useful for mediation models?

So my issue is as follows:

When I specify the following model in Lavaan, using DWLS estimation (due to ordinal factors and mediators):

outcome ~ a*fact1+fact2+fact3+fact4+fact5+fact6+b*med1+c*med2 # DIRECT EFFECT

med1 ~ a2*fact1+fact2+fact3+fact4+fact5+fact6

med2 ~ a3*fact1+fact2+fact3+fact4+fact5+fact6

#indirect effect(s)

indirect_mod1:=a2*b

indirect_mod2:=a3*c

#total effect(s)

total_crp:=a +(b*c)

I fail to meet the thresholds for the fit statistics, but the modification indicies suggest allowing covariance between mod1 and mod2, or one predicting the other (which technically could make sense), however, this then renders my model saturated and the fit statistics become useless.

Any ideas what I can do please? The output of the model is interesting, but I am concerned that the fit is too far off, but can't think of any other way to assess mediators without SEM. I have tried looking at the model-implied (fitted) covariance matrix and the residuals of a fitted model, but I cant see anything drastically out of the ordinary there.

Below are Fit outputs for both the model before mediator covariance and after, for reference.

**Unsaturated model:**

lavaan 0.6-7 ended normally after 53 iterations

Estimator DWLS

Optimization method NLMINB

Number of free parameters 54

Number of observations 9619

Model Test User Model:

Test statistic 35.907

Degrees of freedom 1

P-value (Chi-square) 0.000

Model Test Baseline Model:

Test statistic 474.621

Degrees of freedom 24

P-value 0.000

User Model versus Baseline Model:

Comparative Fit Index (CFI) 0.923

Tucker-Lewis Index (TLI) -0.859

Root Mean Square Error of Approximation:

RMSEA 0.060

90 Percent confidence interval - lower 0.044

90 Percent confidence interval - upper 0.078

P-value RMSEA <= 0.05 0.138

Standardized Root Mean Square Residual:

SRMR 0.009

Parameter Estimates:

Standard errors Bootstrap

Number of requested bootstrap draws 1000

Number of successful bootstrap draws 1000

**Saturated model:**

lavaan 0.6-7 ended normally after 54 iterations

Estimator DWLS

Optimization method NLMINB

Number of free parameters 55

Number of observations 9619

Model Test User Model:

Test statistic 0.000

Degrees of freedom 0

Model Test Baseline Model:

Test statistic 474.621

Degrees of freedom 24

P-value 0.000

User Model versus Baseline Model:

Comparative Fit Index (CFI) 1.000

Tucker-Lewis Index (TLI) 1.000

Root Mean Square Error of Approximation:

RMSEA 0.000

90 Percent confidence interval - lower 0.000

90 Percent confidence interval - upper 0.000

P-value RMSEA <= 0.05 NA

Standardized Root Mean Square Residual:

SRMR 0.000

Parameter Estimates:

Standard errors Bootstrap

Number of requested bootstrap draws 1000

Number of successful bootstrap draws 1000

Thank you so much for taking the time to read my question

Hello everyone,

I am currently working on an indentation and scratchin simulation and everything works very well for a depth-controlled simulation (e.g. the indenter is pushed 100 µm deep into the sample, simply by a BC). I am working with Abaqus 2019.

However, when I want to transfer this model into a load-controlled state, I get major problems. But since indentation and scratch-testing in reality is load-controlled, I want to have it that way.

One of the things I came across is that Abaqus tells me that I would have to constrain the indenter in every degree of freedom, or assign a mass to it. The first suggestion can't be the solution as the indenter has to move, obviously. But if I assign a mass point mass to the RF of the Indenter, I have to guess the mass, because the real mass of a diamond indenter-tip can't be the correct mass here, as it would be only a few grams. That is not the only Problem I came across. Somehow my contact definitions seem to fail and the indenter intersects with the samples surface.

It seems that all tutorials and examples on the internet are depth-controlled and the load-controlled variant is not discussed at all. I found papers where a load-controlled simulation is used, but they dont go into details about their general model design.

So here my question:

Has one of you done a load-controlled simulation of indentation, scratching or a similar process and/ or could share some insight or .inp-file with me?

In a liberal democracy, there is a free market, and in a free market big tech has the freedom it needs to maximize profits even when their actions are not socially and/or environmentally friendly. Big tech can spread easier around the world in countries under liberal democratic structures as the risk of expanding and operating freely there is technically small, rarely futile, than in places where there are non-liberal democracies where the risk of operating freely is very high, even futile.

Usually democracies have been defended by ordinary citizens during elections, not by big tech, but since 2016 and more after the covid19 pandemic big tech has taken a bigger role as it has been expected by their costumer to do so to promote and protect democratic rights using their economic muscle, specially the right to vote/participate, as the case of the USA shows.

Now it seems to be that big tech has realized that profits are more secure the better democracy works, and profits are more at risk when democracy is at risk or when there is no democracy or when democracy ends. They seem to know now that the stability of freedom of operation and expansion is directly related to the freedom that comes from operating under a true democracy.

In other words, current dynamics seem to show that true democracy to succeed needs the support of big tech and big tech to continue to succeed freely needs the support of liberal democracy.

If acting in a coordinated way, big tech can have a huge impact on the political systems inside which they work, be it democratic spaces or non-democratic spaces, which raises the current question, true democracy and big tech, do they need each other now more than ever to succeed locally and globally?.

I think yes, what do you think?

I am conducting my psychology honours project, and for my results I have to run quite a few t-tests. However, I also have quite a strict word-count for this section too. To save myself from saying:

"Data were tested for normality with x test and homogeneity using y test"

Or could I report all the results in a table showing t-values, degree of freedom and the significance, say in the columns and what data the test was run on for the rows?

Thank you!

HiI'm working on a 3D CFD model with Comsol 5.4 and tring to increese de number of elements but im runing low on RAM (i have 32GB of RAM working with an i7-4790). Im using P1+P1 (first order discretization for pressure and velocity fields) the mesh elements and DOF reported en the messege window are:

- Complete mesh consists of 697500 domain elements, 91570 boundary elements, and 2682 edge elements.
- Number of degrees of freedom solved for: 2787596 (plus 5292006 internal DOFs).

And the log reports at the end of the simultion:

- Solution time: 4356 s. (1 hour, 12 minutes, 36 seconds)
- Physical memory: 26.61 GB
- Virtual memory: 28.37 GB

I`m using the default solver configuration. Fully coupled, algebraic multigrid, GMRES solver.It seems to me that it's using more RAM than it should, and i wonder if it has anything to do with the internal degrees of freedom. I don't really understand what they are, and I can't find anything about internal DOF. I woud like to know if they use same amount of memory as regular DOF. And if is a way to reduce them.i'll appreciate any information about this, any other thoughts on the subject or if you can tell me if i having a wrong idea about it and my memory usage is normal

For a few years now, I have dedicated a part of my research and publications to the problem of hate speech on social networks. I am currently outlining a new article on that. There is something that makes me worried. It seems obvious that there are easily labelable and traceable hate speeches (especially in cyberspace with the help of automatic word processing software). Many published works provide today relevant data that allows detecting hate speech and identifying potentially criminal users masked under pseudo anonymity.

My concern is whether there would be another way to better approach hate speech without departing from purely scientific objectives, without contributing to the materialization of a kind of Linguistic Court willing to rule on the acceptability of expressions, perhaps in order to

*cleaning, fixing and giving “splendour*” to digital language, improving, incidentally, the public image of social platforms and regulating the coexistence in cyberspace in such a way that only “good people” could participate ?The truth is that, in addition to those speeches that explicitly express hatred, there is an untraceable, ungrammaticalizable hatred that resists both Logic and Empiricism. The question I ask you is if there is someone else who, like me, fears the risks of such practices of identifying "bad speeches" that could be used to purify the language, limiting freedom of expression? (sorry for my English, which is a language I use very rarely)

I need to understand if the criminalization of homosexuality was introduced by the settlers or Christians. How did Africans perceive non-hetero sex?

Hello,

I am currently performing a coupled field analysis. It is an analysis of an Active Magnetic Bearing in APDL. In the coupled field analysis guide, it is mentioned that for Boundary conditions in a structural-electromagnetic and Structural-stranded coil analysis, the VOLT and EMF degrees of freedom need to be coupled. I have attached a scrrenshot from the guide for reference (Img1).

I would like get some clarity on this . Does coupling of VOLT DOF mean that I have to specify a voltage on a single node of the coil and the couple all the nodes of the coil or is it that I have to input a voltage to the entire coil component and also specify a coupling constraint? Could someone please explain this coupling procedure. I have attached an image of the geometry of the coil structure that I am using. Also, when it is said that VOLT and EMF degrees of freedom must be coupled, both voltage and emf has to be input or either can be input?

Screeshot of coil geometry attached.

Hello Everyone,

I intend to carry out piezoelectric simulations in ABAQUS. For that I am coupling mechanical and electrical field. But the problem is how to couple electric voltage (EPOT) between upper surface and lower surface. In ANSYS APDL, we have direct couple DOF option enabled which couples the Upper surface nodes and lower surface nodes. But in ABAQUS I found it's quite difficult.

Does anybody working on ABAQUS has any idea to above problem? If anybody has any paper or video, please share.

An early reply is highly appreciated. Please do needful.

Thank You !!!

Hi there! I recently came across this question and just couldn’t figure it out.

I have to derive a ANOVA table from the following data:

**_____B1___B2___B3**

**A1__35___32___29**

**A2__29___28___27**

A is a between-participants IV with 2 levels. B is a within-participants IV with 3 levels.

Each cell represents the mean of 10 observations. SSTotal is 1520 and no other information (SD, subjects mean...) is available.

I am given a table as following:

**_____________SS___df___MS___F**

**_____A_______?_____?____?____?**

**_____B_______?_____?____?____?**

**____AB_______?_____?____?____?**

**__A Residual_?_____?____?____?**

**__B Residual_?_____?____?____?**

**_AB Residual_?_____?____?____?**

**____Total___1520__59**

For the non-residual parts I’m fine and have come to these results:

**______SS___df___MS**

**__A__240___1___240**

**__B__160___2____80**

**_AB__40____2____80**

Given SST=1520, I know the total residual must be 1520-440=1080.

I also know the degree of freedom of A Residual = subjects - A levels = 18, and since this is a mixed design AB Residual can be identical to B Residual with a degree of freedom = 36. But how do I partition the total error (1080) to these two parts (A & B)?

Thank in advance to anyone who can help!

Hello,

I've performed a Mantel test between my microbiological data and the geographic distance where those samples were collected, using a table with 516 samples. However, the test doesn't provide the degrees of freedom (df), so I'm trying to calculate it manually.

In a simple test, the df = sample size - 1, while in a correlation test, it is df = sample size - 2. In the case of the Mantel test, the correlation is not between two samples or columns, but between all the 516 rows present in the table. I found different ~possible~ answers, but none of them was clear or objective regarding its calculation. For example: http://www.pelagicos.net/MARS6300/lectures/MARS6300_Lecture21_sp2018.pdf (Mantel test output - TEST STATISTIC: t-distribution with infinite degrees of freedom using asymptotic approximation of Mantel) and (https://v8doc.sas.com/sashtml/stat/chap19/sect42.htm#:~:text=In%20general%2C%20the%20number%20of,%2C%20df%20%3D%20q%20%2D%20t.)

I'm using the mantel() function in R, from the vegan package, with the "spearman" correlation method.

Any help is appreciated! Thank you so much

Adriana

I would like to know if anyone knows clothes used for emancipation like Bloomers, or people who fought for women freedom like Flappers!

I have tried to do a blind docking through Achilles online software as a first approach because I don't know the binding site of my receptor. The problem is that my ligand seems to have more than 12 torsional degrees of freedom and the software asks for less. I have tried to minimize them through Autodock Tools setting them to 12 (the limit for the software) and saved the file as pdbqt but when I upload it, it gives me the same error message again. I think I am doing something wrong. Is there a way to minimize the torsional degrees of freedom of my ligand and then upload the file? Does someone have a suggestion of how can I do blind docking else-wise? Forgive me but I am very new at this.

The ultraviolet behavior of quantum Yang – Mills theory possess no instability as the separation between physical gluons becomes exceedingly smaller & smaller with increase in energy. Ultimately, at quantum length, in the limit of approaching the origin of field space, the dynamical variables, becomes so infinitesimal in magnitude that they effectively represent a single physical gluon G . At Gribov horizon, application of Gauss Divergence theorem to this single physical gluon G leads to singularities of color-Coulomb potential spread all over a spherical surface β at quantum length of physical gluon.

After acquiring additional degree of freedom in the form of free color-Coulomb potential at Gribov horizon, the gluon ‘G’ has the aforesaid spherical system β firmly attached to it. At Gribov horizon, the uncertainty principle forbids this spherical system β, of constant radius (h’/8π), to undergo any Lorentz – Fitzgerald contraction in laboratory inertial frame and rather, demands the motion of gluon ‘G’ to instantaneously drop to zero speed in the laboratory inertial reference frame. This sudden deceleration in the speed of gluon ‘G’ at Gribov horizon assigns an inertial mass to gluon ‘G’ in accordance with General Relativity theory. This inertial mass of gluon ‘G’ produces gravitational effect in its surroundings because of equivalence between inertial mass & gravitational mass in General Relativity theory.

For further details, please click the following link.

I have estimated the parameters by Maximum Likelihood Estimation (MLE) and Probability Weighted Method (PWM). I wish to construct the L Moment Ratio diagram, to graphically demonstrate that empirical (L-skewness, L-kurtosis) coordinates of my financial asset sample lie close to GL distribution (say), but the picture is very clumsy in R. I want to customize it, make it neat and hence i need the freedom to work in spreadsheet. Besides, an excel sheet is more intuitive. Could you kindly sir share it? I shall be grateful to you. I am willing to cite you this work in my reference, and put in in my acknowledgement section of thesis which I shall send you a copy by next July. Please.

I am doing frequency analysis of an orthotropic bridge. To connect the girder with girder, floor beams and edge beams, I assigned MPC constraints to the respective nodes. But after running the analysis, I am getting the following error:

"22 nodes are missing degree of freedoms. The MPC/Equation/kinematic coupling constraints can not be formed. The nodes have been identified in node set ErrNodeMissingDofConstrDef."

I checked again the constraints, but there was not any node with missing dof.

Anyone can suggest me solution? It will be appreciated.

How can I calculate and report degrees of freedom for repeated mesure ANOVA?

I have 48 observations N=48 and 2 factors of 3(P) and 8(LA) levels.

I calculate degrees of freedom as follows:

dF P = a-1= 2

df LA = b-1= 7

df LA*P =(a-1)(b-1)= 14

Error dF P = (a-1) (N-1) = 94

Error dF LA = (b-1) (N-1) = 329

Error dF P*LA = (a-1)(b-1)(N-1) = 658

My JASP analysis gave me these results:

Within Subjects Effects

Cases Sum of Squares df Mean Square F p η²

P 1.927 2 0.964 33.9 < .001 0.120

P*LA 8.450 14 0.604 21.2 < .001 0.528

Residuals 0.454 16 0.028

Can I write P : F(2,14)= 33.9

and P*LA: F(14, 658) =21.2 ???

Or is it P: F(2, 16)=33.9

P*LA: F(14, 16) =21.2 ???

Thanks to anyone who would like to answer

Hello.

I am using ANSYS mechanical APDL.

I currently follow the procedure described in

I wish to add (measurement) noise to all degrees of freedom when performing a harmonic analysis of a structure.

How can I do this? Is there a function which can do this, or is it necessary to apply loads to all degrees of freedom?

I will supply any necessary information you may need.

Thank you in advance!

Kind Regards

Christoffer