Science topics: Correction
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Correction - Science topic

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I want to confirm if what I searched is correct. Thank you!
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Organizational planning and development involve the use of various models, frameworks, and approaches to analyze, design, and implement strategies for improving organizational effectiveness, performance, and sustainability. Some of the key models in organizational planning and development include:
  1. SWOT Analysis: SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis is a strategic planning tool used to identify and analyze the internal strengths and weaknesses of an organization, as well as external opportunities and threats. SWOT analysis helps organizations assess their current position and develop strategies to leverage strengths, mitigate weaknesses, capitalize on opportunities, and mitigate threats.
  2. PESTLE Analysis: PESTLE (Political, Economic, Social, Technological, Legal, Environmental) analysis is a framework for analyzing the external macro-environmental factors that can impact an organization's operations and performance. PESTLE analysis helps organizations understand the broader context in which they operate and anticipate potential opportunities and threats arising from changes in the external environment.
  3. Balanced Scorecard: The Balanced Scorecard is a strategic management framework that translates an organization's vision and strategy into a set of performance measures across four perspectives: financial, customer, internal processes, and learning and growth. The Balanced Scorecard helps organizations align their strategic objectives with key performance indicators (KPIs) and monitor progress towards achieving strategic goals.
  4. Force Field Analysis: Force Field Analysis is a decision-making tool used to identify and analyze the forces driving change (driving forces) and the forces resisting change (restraining forces) within an organization. By understanding the factors influencing change, organizations can develop strategies to strengthen driving forces and overcome restraining forces to facilitate successful organizational change initiatives.
  5. Organizational Development (OD) Interventions: Organizational Development (OD) interventions are structured activities or interventions designed to improve organizational effectiveness and facilitate change. Examples of OD interventions include team building, leadership development, process reengineering, and cultural change initiatives. OD interventions aim to address specific organizational challenges or opportunities and promote continuous improvement and innovation.
  6. Kotter's 8-Step Change Model: Developed by John Kotter, the 8-Step Change Model provides a structured approach for leading organizational change initiatives. The model consists of eight sequential steps, including creating a sense of urgency, forming a guiding coalition, developing a vision and strategy, communicating the change vision, empowering broad-based action, generating short-term wins, consolidating gains and producing more change, and anchoring new approaches in the culture. Kotter's model emphasizes the importance of effective leadership, communication, and stakeholder engagement in driving successful organizational change.
  7. Appreciative Inquiry (AI): Appreciative Inquiry is a strengths-based approach to organizational development that focuses on identifying and building upon an organization's positive attributes, achievements, and successes. AI involves asking generative questions, fostering dialogue, and co-creating a shared vision for the future. By leveraging strengths and positive experiences, AI aims to inspire and catalyze organizational change and innovation.
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Hello, everyone!
I got a very weird shape of volcano plot with R. It doesn't have a typical shape and I want to figure out the reasons behind this problem.
In my plot, I found there were some some long gaps inside the Volcano plot without any dots. It seems that the data was not continuous.
However, I checked adjust p values ,they were continuous.
I couldn't understand how these gaps generated. I am sure the R code is correct.
I am wondering that it might be some thing wrong with my data processing. But I have no hint where this problem came from.
Any suggestions are welcomed!
Thank you in advance!
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It's a bit strange to plot adjusted p-values in a volcanoplot... but that's a different topic.
Please use a logarithmic y-axis or log adj.P in your second plot to make them more comparable. Otherwise the gaps you see in the vocanoplot won't be visible in the lower plot.
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This is the first of a series of postings where I try to correct Physics.
Einstein's Relativity is a useful model that has lasted 118 years. It kept an original sin in Physics: the inability to see a fourth spatial dimension.
That failure is spotlighted in the current "understanding" of the Twin Paradox.
Currently, one assigns the different aging to the accelerated sections of the Traveling Twin. I showed that that is wrong. One cannot assign the slowed aging of the Traveling Twin to the accelerated sections. There is nothing magical about them.
An unbiased view of the Twin Paradox will show that Relativity is intrinsically wrong.
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There's no ``twin paradox''. One of the twins follows a geodesic in spacetime; the other can't, because the solution of the geodesic equation is unique, so it must follow another curve between the same spacetime points.
The geodesic between two spacetime points maximizes the proper time, so the proper time along any other curve is less than hat along the geodesic.
Furthermore, proper time is invariant under global Lorentz transformations, that's why the geodesic isn't equivalent to any other curve and no two curves are equivalent, since hey can't be mapped one to another by a global Lorentz transformation.
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old critical methods , new phenomenon.
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Depends. Science must be falsifiable. My policy stems from tradition, secondly risk analysis and thirdly skin in the game: https://www.researchgate.net/publication/380427514_Kalergi_and_Hart-Cellerand_Memetics_White_Antifragility
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How we make 95% CI (lower and upper) far, when overlap in analysis, whether we can use effect size to make difference in lower and upper interval
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I do not understand. Can you give an example?
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The reference in ResearchGate of our paper is wrong (see joined image). This wrong reference is also visible in the Google website.
The correct reference (Doi number 10.3390/land13050592) is in the Google scholar website, hal-cnrs website (hal-04566042, version 1), and in my ORCID site (https://orcid.org/0000-0002-3411-2647)
Please correct this wrong reference in ResearchGate. I tried to correct it yesterday, but it remains wrong
Best regards
Marianne Cohen
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Could you provide the link you refer to (with the 9 authors)? Since I cannot find it.
What I can find is that (in part?) it has to do with the fact that the paper entitled Resilience of Terraced Landscapes to Human and Natural Impacts: A GIS-Based Reconstruction of Land Use Evolution in a Mediterranean Mountain Valley is missing the proper details (like doi, journal title, issue nr. etc.).
The mixed up with the 9 unrelated authors is most likely due to the fact that your paper is part of a special issue https://www.mdpi.com/journal/land/special_issues/resilience_historical_landscapes (where the second paper is the one with the nine authors).
Best regards.
As indicated by Wolfgang R. Dick claim authorship of the other link (and remove it)
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Or how to create a citation and reference using information available in a paper?
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I like the Purdue Owl reference center for help with citations. https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_style_introduction.html. They describe how to use all the main approaches, like APA, MLA, Chicago.
If you have a reference already needing better citation, ask AI. Try Chat GBT and tell the site what style you want the reference in. Good luck
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There is a serious problem about the authors of a recent publication of my reasearch team. Wrong authors have been automatically registred in ResearchGate : Angelo Castrorao Barba, Pilar Diante-Blasco, Manuel Castro-Priegi, Giuseppe Bazan, etc...
I removed these wrong names yesterday, and I put the correct names as in the following reference:
LE VOT, T.; COHEN, M.; NOWAK, M.; PASSY, P.; SUMERA, F. 2024. Resilience of Terraced Landscapes to Human and Natural Impacts: A GIS-Based Reconstruction of Land Use Evolution in a Mediterranean Mountain Valley. Land 2024, Special issue Resilience of Historical Landscapes, 13, 592. https://doi.org/10.3390/land13050592
Unfortunately the error is remaining in your database, and I received this morning a mail referring this paper as written by Castrorao et al. (see joined image). This error is only found in the ResearhGate system, the Doi number is correct, the reference has been saved correcty in the Hal-cnrs system (hal-04566042, version 1), with my ORCID number (https://orcid.org/0000-0002-3411-2647) and on the Google scholar website.
On the Google website, wrong references from ResearchGate are mixed with the correct reference by MDPI, the errors refer to the name of the authors and to the title.
Please, could you solve this problem urgently, delete these wrong references in your system, and change the number of reads and recommandations to my account ?
Thank you in advance
Marianne Cohen and co-authors
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Please note that you wrote to the ResearchGate community, not to the RG team. However, it is not worth writing to the team. They receive too many such requests. Note that it may last a little bit longer than a day to change the list of authors. Did you follow the instructions in https://help.researchgate.net/hc/en-us/articles/14292798510993-Authorship (section "Adding, editing, and removing co-author information")?
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Panel Error Correction Model (PECM) not the model Panel Vector Error Correction Model
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There are several textbooks and academic papers that discuss the Error Correction Model (ECM) using panel data. One notable reference is "Econometric Analysis of Cross Section and Panel Data" by Jeffrey M. Wooldridge, which provides a comprehensive overview of panel data analysis techniques, including ECMs.
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Dear Researchers,
I am reaching out to you for your invaluable expertise in designing a questionnaire for an upcoming research project
My research focuses on exploring the strategies utilised by translation teachers in addressing errors within the classroom setting, as well as their perceptions regarding the efficacy of error correction techniques. Given the complexity and significance of this topic, I believe that your insights and guidance would greatly enhance the quality and depth of my investigation.
Your experience and expertise in translation didactics research would be invaluable in shaping the structure and content of the questionnaire, ensuring that it elicits meaningful responses and provides valuable insights into the research questions at hand.
Thank you for considering my request.
Warm regards,
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What do you want to know from the questionaire? How many aspects of the issue are there? Who will find the results useful? Do you have an open-ended response in addition to the questionaire? Will you be establishing reliability and validity of the instrument? How will you conduct the sampling, randomly or otherwise? Will results be published or be used internally only?
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Dear Researchers,
I am reaching out to you for your invaluable expertise in designing a questionnaire for an upcoming research project
My research focuses on exploring the strategies utilised by translation teachers in addressing errors within the classroom setting, as well as their perceptions regarding the efficacy of error correction techniques. Given the complexity and significance of this topic, I believe that your insights and guidance would greatly enhance the quality and depth of my investigation.
Your experience and expertise in translation didactics research would be invaluable in shaping the structure and content of the questionnaire, ensuring that it elicits meaningful responses and provides valuable insights into the research questions at hand.
Thank you for considering my request.
Warm regards,
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Error correction is like a light in a dark forest that guides the instructor to clear additions to the curriculum. Errors corrections are lessons for the entire class or to the tutee. Errors a important to clear up.
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My Hirsch index is incorrect - it is 5 not 4. can you please correct it?
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Dear Wolfgang,
What made you answer to my complain? Do you really think your constatation of fact (" The Hirsch index is calculated automatically from the identified citations, and these identifications are also made automatically) is necessary? It is look like a teacher give a lesson to a bad egg student. Exactly this your so called "authomatic" calculation was made with broken calculator. Hello, my complain is addressed to replace this obviously broken calculator. Either or it need to take off option of "Stats" ( for reason of accuracy) or make it accurate. Don't you get it? Is there any logic in your thought? You're making fool of yourself - not helping.
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If a 3D protein is obtained with the inhibitor complex, its wild-type size may change completely. In this case, it seems correct to investigate the binding mode with the inhibitor molecule. If the protein to be investigated has only an inhibitor complex, what protein should I select in the PDB and in my activator molecule research, and what path should it follow?
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Nail Besli Yes you are absolutely correct about the change in conformation of the protein when bound to two different molecule types. However, if you have no structural information available for the conformation with the activator, but have the information for the inhibitor binding.
Molecular dynamics can be a good way to gain some insights of how these conformations change when your protein is unbound (WT), bound to inhibitor and bound to the activator.
This comparative analysis of the structural transitions on a free energy landscape may provide you with detailed conformational transitions that are playing roles. It might be external factors too like salt concentration, pH temperature and so on.
Further, you may use this information to validate your results experimentally and if the changes are adequate you can measure them using fluorescence spectroscopy and circular dichroism spectroscopy experiments.
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Hi all!
I have to quantifiy some proteins in RBCs by ELISA. Since RBC number cannot be standardized and it obviously affect the results, there is the need of some normalization. I read that many groups normalize for total protein content measured by CBA assay. However, I was wondering whether I can normalize my values by using haemoglobin, which accounts for 98% of total proteins in RBCs. For me, it would be far less time and sample consuming, since I would use a spectophotometer and very few microliters of sample, but I would like to know if someone ever used this normalization and if can be considered as correct and reliable.
Many thanks in advice!
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thanks for your kind and thorough reply.
In RBC, I am actually looking for proteins to be used as biomarkers for diseasese not related to RBCs. Therefore, RBCs for me are just a biological matrix, and the proteins I am going to investigate should be not related to RBC function. I can consider my sample as sufficiently pure, since I careflly wash it many times to remove serum and carefully remove the white ring of leukocytes. The reason why I would like to normalize for haemoglobin content instead of total protein is because, as you mentioned, it is simpler, faster, more standardized and requires far less amount of sample.
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I presume that the first author later uploaded the paper given below
Van Gorp, W. and Sevink, J. (2024): The Middle to Late Holocene in the Agro Pontino and Fondi Basin (Lazio, Italy), around the time of The Vesuvian Avellino eruption (ca. 1900 cal BC): A palaeogeographical overview. Palaeohistoria 63/64 (2022/2023), 37-56. https://doi.org/10.21827/662a4aaf39457.
This is the correct citation since it has been digitally published in April 2024
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See the section "Why are there duplicate research items on my profile?" in the help page https://help.researchgate.net/hc/en-us/articles/14293081125777-Reviewing-editing-and-featuring-your-research to get instructions how to merge two entries. And see https://help.researchgate.net/hc/en-us/articles/14293099743121-How-to-make-content-private-or-remove-it.
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Hello,
I am the author, as is Anne-Françoise Dusart, but our names do not appear on the technical report. How can we change this?
Thank you
Joëlle Mottint
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Yes, Yes, we've just solved the problem. Thank you very much.
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One of the authors names appear wrongly or I don't know how. So i'm kindly asking your support so as to replace his name with eth correct author name.
Wrong Name: Mohamed Sharaf
Correct name: Nadia Mohamed Sharaf
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See "Adding, editing, and removing co-author information" in https://help.researchgate.net/hc/en-us/articles/14292798510993-Authorship for instructions how to correct this.
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I have written UMAT and it is showing correct results for tensile loading (displacement) in both (X and Y) directions. But under shear loading (shear displacement) it is not working.
I am attaching the results for all three cases. Please guide me how to resolve this problem?
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can you give some more details? Are those shell elements or solid elements?
How do you calculate the tangent stiffness matrix? Is the indexing of the stress/strain/stiffness tensor that you are using, correct?
For example if the shown model contains CPS4 (plane stress) elements, then you must specify a 3x3 stiffness tensor and 3x1 stress/strain arrays. In case of CPE (plane strain) elements then 4x4 and 4x1, and in case of solid elements 6x6 and 6x1 respectively.
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I am doing some adsorption on the surface and would like to correct the total energies
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The castep calculation is done with the phonon spectrum checked, and the zero-point vibrational energy is derived from a direct thermodynamic analysis after the calculation is complete.
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Hi everyone,
I wanna know about creating the Liquid crystal model in CST.
I used Macros/ material / full tensor material. Is that the correct way for defining liquid crystals in CST?
Your help would be appreciated!
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Yes this is correct way to define liquid crystals through Macros/ material / full tensor material in CST.
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xx
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Spin-orbit splitting energy may be proportional to |dV/dr| at the electron's position. The potential V of an atom is different among different valency although it is very small. We must note that another interaction between (2p spin) and (3d spin), which is smaller but still observable. If we observe 2p3/2 and 2p1/2 peaks of Na3VO4(s=0), VOSO4(s=1/2), V2O3(s=1), then we expect Na3VO4 should be zero spin-spin interaction, but experimentally 2p1/2 is broadest in spite that 2p3/2 is narrowest amongthe three vanadium compounds as mentioned in my book: "X-Ray Spectroecopy for Chemical State Analysis", DOI: 10.1007/978-981-19-7361-1_3
The statement is correct, but the nature is deeper than this statement.
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Hi everyone,
Do you think it is correct to use different protocols of STZ injection to achieve a comparable levels of hyperglycemia in both male and female mice since the later is more resistant to diabetes?????
Thanks
Sherif
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Metabolic disorders occur due to our bad habits of eating process. Like food, water, and liquids, etc. Due to mutations in all our food in saliva, the imbalance of minerals in our body parts and some parts of our body and endocardial gland malfunction. If we do not change our habits, then we will feel difficulties, and these habits, abnormalities, and things are going to our inborn children. And problems are increasing day by day. We are seeing that our inborn children suffer from metabolic disorders from birth, like diabetes, etc. These habits, abnormalities, and genes we cannot correct with any medicine, substitutes, or research like stem cells, gene therapy, etc. "Habits Is a Second Nature “I request all people. Please read my book and follow the eating rules. Then we can achieve victory over metabolic disorders. I welcome all of you at these links:- https://www.lulu.com/shop/innovator-pramod-stephen/your-health-is-in-your-mouth/paperback/product-zgvvk6.html?page=1&pageSize=4 https://www.flipkart.com/aapka-swasth-aapke-muh-me/p/itm22edae101e74a?pid=9789393385543
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I would like to know if Mitutoyo objectives (specifically Mitutoyo Infinity Corrected Long Working Distance Objectives) can be put into vacuum (10^-5 mbar) and without detoriating their performance or destroying the objective.
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Nikon LDW objectives survived. I do not think inside are some kind of liquid, air chamber which would be sensitive to presure changes, but the best way is to ask producer.
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I am analysing data from hippocampal cellular models I have 12 conditions and 3-6 technical replicates and 3 biological replicates. I have a few questions, what correction method do I use for multiple comparisons (i was told bonferroni)?, is 12 too many conditions for multiple comparisons will this always dilute my signfigance?
Can I subset my data which I think is sigificant and do the pairwise t tests on those or is that poor statistical approach?
Furthermore using % change comapred to control is that okay and can I do ANOVA and multiple comparisons on that or is it considered poor approach because there is positive and negative values and some of my standard errors of mean are crossing 0?
What happens if I dont adjust ? I understand the technical increase in false positives but each comparison is testing the effect of likely a different hormone in my case so why do I need to adjust ?please help I am very lost trying to see if there is any signifigance in my data.:)
more info:
I am measuring cytokine concentrations in the supernatant and also measuring % proliferation marker positive cells within total cells for each well , and %apoptosis marker positive cells total cells for each well, and total number of cells.
the 12 conditions are each applied on one biological replicate each having 3 technical replicate (3 wells of the same treatment) from one flask this is then repeated for 2 other biological replicates from separate flasks .
the Conditions are 3 different hormone treatments, and an inflammatory stimulus each with a Control without the inflammatory stimulus. as well as cotreatment Of the hormone treatments so. Condition 1 is control no
hormone , condition 2 control with inflammatory stimulus No hormone, condition 3 hormone 1 without inflammatory, condition 4 hormone 1 with inflammatory. Hormone treatments 2 and 3 are variations in concentration of one hormone. so the same is repeated for them individually as hormone 1 and they are each cotreated with hormone 1 as well so, condition 8: hormone 1 + hormone 2 + inflammatory, condition 9 hormone 1+ 2 without inflammatory etc.
what I’ve done is average the technical replicates for each condition so for each biological replicates I have a mean value for both the cytokines and the cellular markers
So with 3 values (from each biological replicate from a. Distinct flask) for each conditon.
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If you grow the cells in 3 wells in parallel, then the 3 wells can be considered three parts of a larger well, so to say. Count the numbers of cells in these three wells and sum them up. Do not calculate proportions from the counts. It's better to use the counts. Do not average these numbers. Use the sums of the counts in the 3 wells as your read-out and use a binomial model.
Since you know the number of cells in each well, you can divide the measured cytokine conc in each well by the number of cells in that well to get the concentration per cell. These concentrations per cell can be averaged over the 3 wells.
This is done for each condition.
As I understood, you have a 2x2x2 design, with the experimental factors:
(i) inflammatory stimulus (no/yes)
(ii) treatment with hormone A (no/yes)
(iii) treatment with hormone B (no/yes)
And as I understand further, the scientifically interesting questions are supposedly if the hormone treatments alter the reaction to the inflammatory stimulus, and, possibly, if the combined treatment effect is different to the sum of the individual treatment effects (that is, there is a synergistic or antagonistic effect of the two hormones). Simple effects may be only interesting to demonstrate or check that the inflammation worked as expected and that the experiment was good enough to see that.
These questions can be addressed in a 2- or 3-factorial statistical model looking for the 2-way and 3-way interactions.
For the cell numbers, these models should be binomial models. If this doesn't work for you, you can calculate the proportions by hand and use the logit-transformed proportions in a normal model. For the cytokine concentration, these models should be gamma, quasi-Poisson or log-normal models (that is: use the log-transformed concentrations in a normal model).
Now what I did not understand is if you used cells from "the same flask" also across different treatments. If so, then you should include the "flask ID" as another factor in your model to account for differences between flasks. It does not matter for your purpose if you model this as a fixed or a random intercept term.
Notably, the only "family of tests" you may consider for multiple testing are the two tests of the 2-way hormone x inflammation interactions. Here a simple Bonferroni-adjustment will do (either double the two p-values or test at a test-wise alpha/2).
If you have no idea what I was trying to tell you here, I strongly suggest consulting a local statistician. You may give her/him this text to get a quick overview of your experiment and a possible analysis strategy.
Good luck
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I wanted to ask for clarification on statistical approaches for a classic 2x2 pre-post design where I measure an outcome in a pre-intervention and post-intervention phase in two distinct groups.
Typically, what we want to investigate in these cases is the interaction, which tells us if the changes over time in a specific outcome differ between the two groups. To do this, we have three approaches available: Repeated Measures ANOVA (RM ANOVA), ANCOVA, and Linear Mixed Models (LMM).
RM ANOVA: It allows us to study the interaction, as well as the main effects of the between-subject factor (group) and the within-subject factor (time). So, besides telling us if there's a different change over time for the two groups, RM ANOVA also informs us if there's a general change over time (disregarding groups) and if there's a general difference between the two groups (disregarding time). However, the issue with RM ANOVA is that it doesn't allow us to covary the score of the outcome in the pre-intervention phase. This means that any significant pre-intervention difference between the two groups could influence the results and make their interpretation much less robust. The solution in this case would be to verify (with an independent samples t-test) that there are no pre-intervention differences between the two groups in the outcome.
ANCOVA with the pre-intervention outcome score as a covariate: It allows us to see if there are differences between the two groups post-intervention. It doesn't tell us if there's a different change over time between the two groups, if there's a general change over time, or if there's a general difference between the two groups. It doesn't evaluate the interaction, the main effect of time, or the main effect of group, unlike RM ANOVA. The advantage of ANCOVA is that it enables us to study the differences between the two groups ONLY in the post-intervention phase, accounting for pre-intervention differences in the outcome. This means that this model works well even in cases of large outcome differences between the two groups in the pre-intervention phase.
Therefore, RM ANOVA and ANCOVA provide quite different information. If there are differences in the outcome in the pre-intervention phase, it's advisable to use ANCOVA (less informative, as it considers fewer effects); otherwise, it's better to use RM ANOVA (more informative, as it considers more effects). Right?
The solution to all of this is LMM because, in addition to considering all the effects of RM ANOVA (interaction + the two main effects), it also models any differences in the outcome pre-intervention. So, is it always better to use an LMM, right? Is everything correct, or am I missing something?
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Yes, I'm referring to a true experiment where subjects are randomly allocated to groups
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Our paper (Surlyk, Alsen, Piasecki, 2024) is referred to as published in n Norsk Geologisk Tidsskrift.
The correct journal title is: Geologisk Tidsskrift. It is a sister journal to Bulletin of the Geological Society of Denmark.
So please correct the mistake.
Best regards
Finn Surlyk
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The problem is that the Geologisk Tidsskrift of the Geological Society of Denmark is not in ResearchGate's database of journals. Therefore, the automated algorithm assigned the journals with a similar title to your paper. See my reply to https://www.researchgate.net/post/How_to_add_Journal_title for a proposal what to do in such a case.
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Dear Colleagues,
We plan to isolate and characterise extracellular vesicles released by dying cells during radiotherapy of head and neck squamous cell carcinoma. Given the duration of radiotherapy (about 6-7 weeks), we are thinking about the optimal time when the maximum wave of cell death occurs in the tumour (Ideally, we'd like to capture the first wave of cell death :)). Do you have any advice on when to take samples after radiotherapy? In this case, would plasma, serum or whole blood be better for the isolation of extracellular vesicles?
Thank you for your answer.
Kind regards,
Jan
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Dear Dr. Jan Balvan
The tumor cell fate decisions such as programmed cell death and non-programmed cell death induced by radiotherapy are related to various factors such as tumor cell type, time and dose of radiation and tumor microenvironment. Radiotherapy does not kill cancer cells immediately, and the tumor cell death may persist for days or even months after radiotherapy.
Some cells may die relatively rapidly through apoptosis. However, most cells do not manifest evidence of damage until mitosis occurs, and several divisions may ensue before actual cell death which is termed as mitotic cell death. This means that the cell dies when it attempts to divide. So, if a cell does not divide, then it does not die, but just sits there. At the same time, if a cell doesn't divide, it also cannot grow and spread. For tumors that divide slowly, the mass may shrink over a long, extended period after radiation stops. For instance, the median time for a prostate cancer to shrink is about 18 months (some quicker, some slower). For colon cancers, some may grow more quickly, and others may grow more slowly and this will affect how they are killed by radiation.
The cellular doubling time which is typically three to five days for head and neck cancer also influences the rapidity with which a tumor will shrink. For this reason, most tumors do not show immediate shrinkage after starting radiotherapy. While radio responsive tumors start to shrink in a few days, most head and neck cancers may take weeks or longer to shrink. Some low-grade, slowly proliferating tumors histologically appear to be viable for prolonged periods after irradiation. So, it would be difficult to predict the first wave of cell death.
To select the optimal time when the maximum wave of cell death occurs in the tumor, I would suggest you include radiological scanning as this would help you to record the tumor shrinkage, which in turn could assist in the selection of the optimal time. However, shrinkage may not always be seen right away even when cells may still be dying in response to radiation, sometimes causing an inflammatory response that can even make a mass look larger.
The second part of your question.
In such case, plasma sample would be better for the isolation of extracellular vesicles. You may collect blood samples in citrate tubes and centrifuge at 1000 x g for 10 mins followed by 2500 x g for 10 mins. Following centrifugation, it is important to immediately transfer the liquid component (plasma) into a clean microcentrifuge tube using a pipette. The samples should be maintained at 2-8°C while handling. If the plasma is not analyzed immediately, store the plasma samples at –80°C in aliquots. Avoid multiple freeze-thaw cycles.
You may want to refer to the article attached below. It may be helpful.
Regards,
Malcolm Nobre
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hi every one
What is the correction factor in the tomato leaf area equation?
leaf area = maximum length of the leaf * maximum width * correction factor
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Maryam Sami Please, read:
Blanco, Flávio Favaro, and Marcos Vinícius Folegatti. "A new method for estimating the leaf area index of cucumber and tomato plants." Horticultura Brasileira 21 (2003): 666-669.
Lee JM, Jeong JY, Choi HG. Estimation of leaf area using leaf length, leaf width, and lamina length in tomato. Journal of Bio-Environment Control. 2022 Oct 31;31(4):325-31.
BEYHAN M, Sezgin UZ, KANDEMİR D, Harun ÖZ, DEMİRSOY M. A model for predicting leaf area in young and old leaves of greenhouse type tomato (Lycopersicon esculentum, Mill.) by linear measurements. Anadolu Tarım Bilimleri Dergisi. 2008 Jan 12;23(3):154-7.
The last one describes this relation as:
Equation 1 "mean leaflet length (MLL) of a main compound tomato leaf and the length of the longest leaflet (LLL) of the top three leaflets of the main compound leaf (MLL(cm)=-0.36+1,02*LLL–0,02*LLL2,
r2=0.98,.
(Equation 2 "mean leaflet length (MLL), longest leaflet length of the top three leaflets of the main leaf (LLL) and longest leaflet width (LLW) of the top three leaflets The leaf area was found as LA (cm2) =31,6–18.41*MLL+2.40*MLL2+0.45*LLL2*LLW,
r2=0.99"
Equation 3 " LA=31.6–18.41*(-0.36+1.02*LLL–0.02*LLL2)+2.40*(-0.36+1.02*LLL–0.02*LLL2) 2 +0.45*LLL2*LLW"
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I have found some methods like clipping and interpolation or hampel filter ...
Is there any other efficient or better methods?
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i have snr values from an mst radar .. however i want to apply the time height range correction of snr values .how can i do that whats the formulae ?
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Here's how the height range correction of SNR (Signal-to-Noise Ratio) applies to MST (Mesosphere-Stratosphere-Troposphere) radar wind profilers:
Understanding the Problem:
  • SNR is a crucial parameter in radar measurements. It represents the ratio of the desired echo signal to background noise. A higher SNR indicates a clearer signal and more accurate measurements.
  • In MST radar wind profilers, SNR can vary with height due to several factors:Beam divergence: As the radar beam travels upwards, it expands, leading to a weaker signal at higher altitudes. Atmospheric attenuation: Air molecules and particles absorb and scatter the radar signal, reducing its strength with increasing range.
Height Range Correction:
  • To account for these variations and obtain a more accurate representation of the actual atmospheric reflectivity, a height range correction is applied to the measured SNR.
  • This correction factor typically increases with height, compensating for the weakening signal.
Methods for Height Range Correction:
There are two common approaches for height range correction of SNR in MST radar wind profilers:
  1. Theoretical Models:Atmospheric models like US Standard Atmosphere (USSA) provide information on atmospheric density and composition at different altitudes. Based on these models, the theoretical signal attenuation due to atmospheric effects can be calculated. This calculated attenuation is then used to correct the measured SNR for each height range.
  2. Calibration Techniques:Radars can be calibrated using targets with known reflectivity at specific heights. By comparing the measured SNR with the expected value for the calibration target, the height-dependent correction factor can be determined. This method is more empirical but can account for real-world factors not captured by theoretical models.
Additional Considerations:
  • The specific method used for height range correction may vary depending on the particular MST radar system and desired application.
  • Some advanced systems may employ more sophisticated correction techniques that account for additional factors like wind shear and antenna characteristics.
Resources for Further Reading:
  • You can find more detailed information on MST radar wind profilers and data processing techniques in scientific publications and textbooks related to atmospheric radar systems.
  • Search for terms like "MST radar data processing," "SNR correction in MST radar," or "height range correction for atmospheric radar."
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I have notice that my last name is misspelled and I would like to change it to the correct one: Monica Torreiro-Casal. Thanks
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please have a look at the following page of the RG help center:
and follow the instruction with respect to edit your account name.
Good luck and
best regards
G.M.
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as above
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Thanks so much Wolgang!Have a wonderful day 😊
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I am relatively new to the genetics field and am curious if their is an established way of representing BAC transgenic mouse models. I know that a homozygous knockout trangenic model is expressed -/- etc. I was just curious if there is a correct notation for the addition of a BAC in a mouse model. Thank you.
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One effective way to represent BAC transgenic mice in a figure is to create a simplified schematic diagram. This diagram should include a depiction of a mouse with labeled components such as the BAC transgene and any relevant promoter regions, along with arrows or annotations indicating gene expression patterns or other key features. This approach provides a clear and concise visual representation of the transgenic mouse model and its essential elements
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It is universally accepted that Arithmetic Mean (AM), Geometric Mean (GM) and Harmonic Mean (HM) are three measures of central tendency of data.
Suppose,
X1 , X2 , ................ , Xn
are n observations in a data set with C as their central tendency.
I am in the thrust of what is the logic or what is the cause for which each of AM , GM and HM is accepted as a measure of the central tendency C.
If I accept the argument that each of
AM ( X1 , X2 , ................ , Xn} , GM ( X1 , X2 , ................ , Xn) and HM ( X1 , X2 , ................ , Xn)
converges to C as n tends to infinity for which they are regarded as measures of C i.e. the central tendency of X1 , X2 , ................ , Xn ,
will it be correct ?
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Dear Doctor
[Arithmetic Mean of Ungrouped Data: There are two methods for calculating arithmetic mean for ungrouped data. i) Direct method ii) Indirect or short cut method i)
Direct method:
Arithmetic Mean (A.M.) =Sum of observations/Number of observations
Indirect or short cut method: In this method an arbitrary assumed mean is used. Deviations of individual observations from this assumed mean are taken for calculating arithmetic mean.
Arithmetic Mean of Grouped Data: There are two methods for calculating arithmetic mean of grouped data.
i) Direct method
ii) Indirect or step-deviation method
Merits of Arithmetic Mean:
i) It is easy to understand and calculate
ii) It is based on all observations
iii) It is rigidly defined
iv) It is capable of further mathematical treatment
v) It is least affected by sampling fluctuation.
Demerits of Arithmetic Mean:
i) It is unduly affected by extreme values.
ii) In case of open ended classes it cannot be calculated.
B. Geometric Mean:
When we are interested in measuring average rate of change over time then we use geometric mean. Geometric mean is defined as the nth root of the product of n items (or) values.
Uses of Geometric Mean:
Geometrical Mean is especially useful in the following cases.
1) The G.M is used to find the average percentage increase in sales, production, or other economic or business series. For example, from 1992 to 1994 prices increased by 5%,10%,and 18% respectively, then the average annual income is not 11% which is calculated by A.M but it is 10.9 which is calculated by G.M.
2) G.M is theoretically considered to be best average in the construction of Index numbers.
C. Harmonic Mean:
The Harmonic Mean (H.M.) is defined as the reciprocal of the arithmetic mean of the reciprocals of the individual observations.
Merits of Harmonic Mean:
1) Its value is based on all the observations of the data.
2) It is less affected by the extreme values. 3) It is strictly defined.
Demerits of Harmonic Mean:
1) It is not simple to calculate and easy to understand.
2) It cannot be calculated if one of the observations is zero.
3) The H.M is always less than A.M and G.M.
Uses of Harmonic Mean:
The H.M is used to calculate the averages where two units are involved like rates, speed, etc.
Relation between A.M., G.M. and H.M.
The relation between A.M, G.M, and H.M is given by
A.M >= G.M >= H.M
Note: The equality condition holds true only if all the items are equal in the distribution.
Summary
The measures of central tendency give us an idea about the central value around which the data values cluster. That’s why these values are considered to be representative values i.e. the values which represent the data. Arithmetic mean is the most common measure of central tendency which is obtained by adding all the observations and then dividing the sum by the number of observations. Geometric mean is used for measuring the average rate of change over time. It is defined as the nth root of the product of n items (or) values. Harmonic Mean (H.M.) is defined as the reciprocal of the arithmetic mean of the reciprocals of the individual observations.]
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My paper (cancer stem cells the need for a correct definition) was withdrawn from Juniper Publishers (no functional DOI, no indexing)and submitted to a new journal.
It must be withdrawn from research gate.
Thank you.
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Dear Friends, wishing all of You a very Happy New Year - 2024
Richard Mueller, the Science Consultant of Rutgers University, NJ, USA has the following to say about my Theory, which is experimental verification:
Surya,
I searched for solar eclipse data, and I picked dates between 1499 to 1403 BC, and I calculated the growth of the sun with corrections of expansion of the atom with the term Mp+/me-, the sun's 11-year solar cycle, the expansion of the universe at 0.9850 C, the expansion rate of the universe at e^1, and the possibility that there are 2 universes. The two universes are our matter universe and the parallel anti-matter universe. I Then compared this growth rate to the Earth that Ruud Loeffen calculated, and I used a correction of 109.2^0.5 because of the 1/r^2 value of gravity in Newton's equation and 5/4 for the moment of inertia because the sun has a much less density than the earth to account for the differences of the sun's and the earth's radii. You value for the expansion of the sun is 31.265 cm/yr. The value from the solar eclipse data came out to 31.109 cm//yr. The value of the Earth from Ruud's calculations from his paper came out to 2.4 cm/yr. The corrected value for the Sun using Ruud's calculations came out to31.349 cm/yr using from what I know from my theory.
You are indeed correct Surya! The sun's age is about 5 billion years, and it takes 5 billion years for a star such as the sun to become a red giant, so the sun is very near to becoming and red giant due to this increase in radius and mass. But try to get a mainstream scientist to agree with your theory and my analysis and they will say we are both nuts to cover this information up. This is why they are building the Helion Fusion Reactor to produce anti-gravity waves to turn back time to reverse this process but don't tell anyone as they are all lied to and very delusional and they will not believe you and yell at you due to the world's governments lying ab0ut science data. This is why the Sun is getting hotter or the climate change as the sun heats up due to increased fusion from the increased mass which will lead to the sun expanding to engulf the Earth and why Elon Musk is building many star ships to move 1 million people to Mars which is outside of the Sun's expansion and why Mars will become like Earth. This is a backup plan if the Helion does not work. But I have my star device being worked on that I am sure will work and save the Earth.
Rick
Dr. Kasibhatla Surya Narayana
5 mos ago
Rick,
Basically, I am poor. I can't invest in any power reactor right now. But, I would like to know whether you consider my Theory to be true and correct, to the extent grasped and understood by you.
Surya
Like
Richard Muller
5 mos ago
Surya,
Yes, I do think y0ur theory is true and correct.
Rick
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According to my findings, the theory of the expansion of the sun and the swallowing of the earth is completely wrong.
According to the new core model I discovered: In the formation of the solar system: the core, the sun must have been perfect in all stages in the beginning.
In general: 1- First, the core of the sun is formed with all the events inside it. 2- The rings around the sun's core are formed at the same time as the sun's core is formed. 3- The formation of the sun's shell, and the definite and permanent completion of the sun. Sun.
4- The formation of planets, in the rings around the sun, which can coincide with the formation of the sun's crust.
Unfortunately, I can't explain further because my findings are not yet registered.
But the adventures inside the kernels are very exciting and fascinating. I made some big tricks that solved the mystery of the universe and matched all the scientific results. It answers all the mysteries of existence. Unattainable tricks and I was very lucky.
In the formation of the nucleus, Kepler's laws are solved fortuitously and no proof is needed.
All in a classic and experimental way. No quantum theory
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A question to the statistics savvy people on
I'm interested to evaluate whether a specific disease state manifests as imaging-derived parameter across a range of ages.
I have 2 samples (+disease/-disease) of about 500 subjects each, across a similar range of ages (40-70)
I played with the data and noticed that for younger subjects the said parameter does not significantly (ttest, p>.05) separates the 2 groups, while in older it does. I was wondering if there is a correct way to determine the critical age (or age range) in which an effect becomes significant. I used a sliding window (8 years) that showed the effect become significant from 47-55 age group onward. I am not sure that this is the correct approach as in the sliding window analysis the samples (i.e windows) are not independent.
Follow-up question – If I want to control for potential confounds such as different ratio of male/female in each sliding window, should I use a GLM?
Thanks in advance
Hope this leads to an interesting discussion.
Greg
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The above two published papers are the only correct proofs of mine on elementary proof for Fermat's last theorem ( attached herewith). Request your valuable feedback please
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I think that they are theorems with clear and uncontradictable explanations
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In a questionnaire, I have some questions whose answers do not have a majority, i.e., all percentages are below 50%. As far as I know, here I can look for the plurality. So I have two questions:
1: Is there one plurality or multiple pluralities?
2: Is it correct to combine categories that represent similar or related sentiments to gain a clearer understanding of the overall trend? For example, when there is a high percentage in the options of "agree" and "strongly agree," is it correct to see the total percentage of respondents who express agreement with the statement, and if so, to say that there's a tendency toward agreement?
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Since your analysis is entirely descriptive, you can set the cut-off points anywhere you like.
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Hello, what is the correct way to express the biomass results measured with a laboratory digital scale? Most scientific works express it as weight, however very few express it as mass,
thank you very much
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To [email protected] Respected, Sir/ Madam I want to draw your attention towards the diabetes eradication program. Diabetes is a metabolic disorder and it is not correct by any Medicine, Substitute, Yoga or Exercise. If possible please tell me. In our body first diabetes1 comes and after some time it changes into diabetes 2 I request you and your team, Please read my book Your Health Is In Your Mouth English https://www.lulu.com/account/projects/zgvvk6 Hindi https://www.flipkart.com/aapka-swasth-aapke-muh-me/p/itm22edae101e74a?pid=9789393385543 I want your company Looking forward to hearing from you soon.
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No, Metabolic disorder not fully cure by yoga, medicine, But if we maintain daily routine, exercise ,control BMI, and intake appropriate food then we can overcome our problem mostly and delay our metabolic complication and we can use herbal medicine (less side effect) to control complication.
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How can I correct wrong entries in ResearchGate, e.g. misspelled author names or citation of the wrong journal?
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See "How do I edit my research item's details?" in https://help.researchgate.net/hc/en-us/articles/14293081125777-Reviewing-editing-and-featuring-your-research for instructions. See also "Adding, editing, and removing co-author information" in https://help.researchgate.net/hc/en-us/articles/14292798510993-Authorship. Concerning the indication of the journal among the bibliographic details, see my reply to this question: https://www.researchgate.net/post/How_can_I_add_the_name_of_the_journal_where_my_article_is_published_when_the_name_of_the_journal_is_automatically_cancelled. My reply contains also a proposal what to do in case of a missing journal title in ResearchGate's database. If you mean wrong citations of other publications: Unfortunately, it is not possible to edit these. Incomplete and sometimes wrong identifications of citations by RG's automated algorithm is a frequent problem.
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The URL assigned for my researchgate landing page is incorrect - it has my name wrong. How do I correct it to reflect my correct name?
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It does not seem possible to change the URL "by hand". My observation is that RG's algorithm compiles the URL from the first and the last names, adding a number in case of dublicate names of users. Cf. the URL of my account: https://www.researchgate.net/profile/Wolfgang-Dick-3
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Good afternoon
How can I find out the full name of my profile and edit it if necessary?
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The first author of this paper is wafa saadi and not wala saadi ? Please to correct this.
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See "A researcher has wrongly claimed co-authorship of my publication" in https://help.researchgate.net/hc/en-us/articles/14292798510993 for instructions how to correct this. But unlike this help page suggests, most probably it was not the other author himself who wrongly claimed authorship, but ResearchGate's automatic algorithm wrongly identified him as the author and assigned your publication to his profile. This is a frequent problem in ResearchGate in case of similar names.
Please note that you wrote to the ResearchGate community, not to the RG team. But it is not worth writing to them because they will give the same advice.
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We have this machine and the temperatures are not correct. Does anyone know how to calibrate it?
Thank you in advance
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V. Ravi I am sorry, it is a thermal cycler by Peqlab.
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I am currently working on a CRISPR Cas9 project that involves preparing DH5a competent cells for bacterial transformation. I conducted heat-shock transformations using PUC19 as a positive control and my samples. In the case of PUC19, I used 2.5 µl with 50 µl of DH5a, while for my samples, I performed the heat-shock transformation twice. Initially, I used 1 µl with 150 µl of DH5a, and in the second attempt, I used 2 µl with 200 µl of DH5a. Unfortunately, I did not observe any colonies in both the positive control and my samples. However, after two nights, I noticed a few colonies only on the PUC19 plate.
I have concerns regarding the DH5a preparation. Firstly, the OD reached 0.569 before diluting it to the optimal density of 0.4. Is that correct to dilute?
Secondly, the ampicillin used had been stored at 4°C for almost 9 months, raising doubts about its effectiveness. Despite this, the absence of bacterial growth without ampicillin indicates that the ampicillin is still active.
I am seeking advice and opinions from experts on this matter. Any suggestions on optimizing DH5a preparation, troubleshooting the lack of colony formation in my samples, and ensuring the effectiveness of the stored ampicillin would be greatly appreciated.
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Try to add,
5µl of DNA and 50µl of DH5α cells thereafter heat shock procedure.
prepare antibiotics before use and add to media at lower temperature.
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I have the survey among three groups of health professionals to answer the survey.
The survey is a Likert scale for seven different treatment options across different disease conditions (6 conditions).
The goal is to assess if there's a statistically significant difference between the mean scores of these different groups of health professionals for various treatment options.
I have 6 different disease condition (or 6 different question) each question with 7 different treatment option.
I am thinking to run ANOVA works here, but if I want to run ANOVA, then will need to run that 42 times. Because (6*7=42)
Then Applying corrections like the Bonferroni correction to adjust for the increased risk of Type I errors (false positives) when conducting multiple statistical tests, such as multiple ANOVAs. But still will need to apply ANOVA 42 times, is that correct method to do for this? Is there Any better method?
if I want to calculate the overall mean score for one specific treatment option across all disease conditions, then will run the ANOVA just seven times.
If I want to go with the first approach, what method do you suggest?
Am I correct to apply anova?
Thanks
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I agree with Hsin-Yuan Chen . MANOVA would be more suitable for your dataset and experimental design. It helps to control the Type I errors more effectively.
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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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Hello,
what is the best way to determine the 19F-NMR yield using mnova as software?
What are the processes I have to do before integration of the internal standard and
product peaks? Which Baseline correction is the best one? Polynominal Fit?
Thank you for any help!
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Choosing the best baseline correction method also depends on what the baseline looks like. 19F-NMR spectra can have a significant baseline roll. If you have a perfectly flat baseline after a polynomial fit, bias and slope correction (linear baseline correction option in Mnova) is not required. If your baseline is not flat, then a linear baseline correction is recommended.
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Hello everyone! I am doing single crystal neutron diffraction of whose structure is known. How can I determine what parameters to look for in a valid refinement for Fcalc/Fobs?
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Hey there Rahul Goel! It's awesome that you're diving into single crystal neutron diffraction. When it comes to validating your refinement, especially with a known crystal structure, there are a few key parameters to keep your eyes on.
First off, check out the R-factor (or R1) and the goodness-of-fit (GOF). These metrics give you Rahul Goel a solid indication of how well your calculated structure matches up with the observed data. A low R-factor and a high GOF are what you're aiming for.
Next up, scrutinize the refinement convergence. Ensure that the refinement process has reached a stable and consistent state. This is crucial for reliability.
Also, don't forget about the thermal parameters (B-factors). They provide insights into the thermal motion of atoms within your crystal structure. If they align with expectations and show reasonable values, it's a good sign.
Lastly, consider consulting with experts or utilizing validation tools and software to double-check your results. Collaboration and verification are key in scientific endeavors.
By keeping a keen eye on these parameters and leveraging available resources, you'll be well-equipped to conclude the validity of your single crystal neutron diffraction refinement. Keep up the great work!
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I'ma writing to you in relation to the following publication:
Gottlieb, Henrik (2022) La semiótica y la traducción, Hermēneus. Revista de Traducción e Interpretación, 24 (2022), pp. 643-675. doi:10.24197/her.24.2022.643-675 [traducido del inglés por Laura Gata González y Anna Kuźnik]
It is a translation from English into Spanish by my student, Laura Gata González, and myself.
The first surname of Laura Gata González, i.e. "Gata" had been badly introduced by the editor of the scientific review, Hermeneus (afterwards it was corrected though), to the doi system and Crossref, actually as "Gato" (and not "Gata"). In consequence, it went to researchgate with its wrong spelling "Gato". How can I correct this?
Please, give me some indications on this.
I have already corrected the wrong spelling of my own surname, but I am not able to do the same with other authors' data.
With my best wishes,
Anna
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As above.
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I've been working on the TiO2 anatase and rutile. the bandgap value is always less by 1 even when I apply hubbard correction.
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There are some strategies to get the optimum values of +U. One such physical quantity is the magnetic moment in case of magnetic systems. Reviews are helpful.
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I was told that I have to post concentrations of primers in µM per amplified DNA sample in the documentation of a qPCR instead of absolute volumes. However, I am not sure how to do that. I used 0.4 µL of both forward and reverse primer with a concentration of 10 pmol/µL. Could you show me how to calculate the correct concentration in µM? I would be very pleased about your support.
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The rule is that: 1µM = 1pmol/µl,
in your case, if you take 0.4 µL of 10µM (10pmol/µl) concentrated primer, the final concentration will be 0.16 µM (160nM) in a final reaction volume of 25µl.
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Both cohen's D and hedges' correction are negative . Does it means that after intervention there was negative effect in the population
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Andrew Paul McKenzie Pegman , no, please look up the definition of g: it is the mean difference, divided by the standard deviation (via the pooled variance estimate). Hedge's modification is only concerning the standard deviation in cases where the sample sized are different. Thus, for both statistics the sign is that of the mean difference.
And regarding your statement "Those corrections merely indicate the size of the difference :)": I don't subscribe her either. The size, directly and simply, is the mean difference. d (and g) give standardized sizes, a rather convoluted measure.
Sudeepa Kumari , you cannot know what the effect is in the population. That's why you do inference. The sample will either have a positive of a negative mean difference. You see this by comparing (i.e. subtracting) the sample means directly, or via d or g (as you did). This may or may not be informative for the population. The larger the sample, the more informative is it (given it's a random sample). The p-value from a test about the hypothesis that the mean difference is zero (usually a t-test) will tell you if the sample size may (or may not) be considered large enough to conclude that the sign of your sample mean difference is the same as the population mean difference (aka the expected difference).
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Hi
i want ot ask if the relation for directivity is correct
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in my last latest paper on earthquake related to Turkey-Syria earthquake , the doi number is types incorrect. How do I correct this?
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Hit on the down arrow More
Then Edit
Change the doing
Then Save
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Researching this I routinely find that both the numbers 35768 km and 35786 km are given. Which one is correct or most accurate ?
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The correct height of the orbit of a geostationary satellite is approximately 35,786 kilometers (22,236 miles) above the Earth's equator. At this height, the satellite orbits the Earth at the same rate as the Earth's rotation, allowing it to appear stationary relative to a fixed point on the Earth's surface. This specific orbit enables geostationary satellites to provide continuous coverage of a particular area on the Earth's surface, making them ideal for applications such as telecommunications, weather monitoring, and broadcasting.
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Hi everyone, I would appreciate to tell me you suggestion:
I’m going to compare just two independent group. The outcome variables are continuous -one of them has 5 subclass and another one has 4 subclass-
I am thinking to apply running separate t-test for each subclass of these outcome variables (to compare total score and subclass score).
Then will consider adjusting for multiple comparisons to control the Type I error rate by Bonferroni correction.
But as I have one confounding variable, so will ignore T-test and apply ANCOVA?
Am I correct, ANCOVA is the best for my goal?
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Excellent method. Thanks for sharing. I was unaware of this unique advantage of logistic regression.
Many Thanks,
Bahar.
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Hi Everybody. I'm senior in a University in Vietnam. This is fisrt time I do SDS-PAGE, so I want to ask about the correction of my loading buffer recipe for SDS-PAGE as a following file.
In addition, If 0.5M Tris-HCl pH 6.8 isn't available, Can I replace it by 1M Tris-HCl pH 6.8 or any other concentrations of Tris-HCl pH 6.8.
Also, how should I mix these components? (In order or out of order)
(Samples I am using in my research is piglet intestines)
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Both answers are correct
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Please, How can I correct an error in the presentation of a publication?
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We ask you to kindly change the information of the first name written incorrectly as Sarah Ayman to the correct name as listed in the article, Ayman S Taha.
Sincere thanks and appreciation.
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Dear Ayman Taha ,
you have to chage your account name by yourself...
For instructions to do that, please go the following RG help-page:
Go to the section 'Changing your account name' and follow the instructions there...
Good luck and
best regards
G.M.
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Many years ago I witnessed a mathematics class in Japan, in which the teacher displayed, to a class of 10 year old students, a narrow strip of paper which she identified as being one meter in length. She then proceeded to distribute one strips of paper to each child in the class, asking them to give her back "a one-half meter length of paper." Most of the students simply folded cut their strip lengthwise in half and returned one of the halves to the teacher. The teacher then placed each child's response (the actual strip of paper) on the blackboard and initiated a discussion about who had given a correct answer. I would like to find a report that refers to this research so I can share it with teachers and mathematics educators. Do you have any suggestions?
By the way, this same sort of confusion between half of the whole and half of the unit frequently appears in discussions regarding the number line. For instance, a child (or teacher) may be unsure where to locate 1/2 on a number line from 1 to 7. So I think it's a very important issue to keep track of.
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The teacher showed one strip of paper and said it was one meter long. I think you could argue that it was being treated as the whole but also as the unit. This would seem analogous to showing the students a number line from 0 to 1 and asking the student to located a certain common fraction on the line (say 1/2 or 3/4). Most young students will place the fraction at the "correct" place under this condition. But when the question is asked using a number line from 0 to 5, many students will simply find the endpoint where one half or three fourths of the number line will fall.
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I have a protein and I want to check the orientation of side chain of a particular resdiue A with respect to the residue B in the active site. any help on this regard? currently I am using gmx gangel where group 1 includes the alpha carbon position of B residue and alpha carbon position of A residue and group 2 includes alpha carbon of B and the last atom of the A residue. I am not sure if this is the correct way. any guidance would be appreciated.
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thank you Te.hmina Khan
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Hello everyone,
I'm trying to extract water surface elevation of a reservoir from Sentinel 3A and 3B. The following equation is used:
H = Alt - (Range + Cdry + Cwet + Ciono + Ctide + Retrack) - Geoid
where: Alt is the satellite altitude, Range is the distance between the altimeter and the lake surface, Cdry is the dry troposphere, Cwet is the wet troposphere, Ciono is the ionospheric correction, Ctide includes the solid earth tide, pole tide, and ocean tide corrections, Retrack is the retracking correction, and Geoid is the geoid height with respect to the ellipsoid (Chen and Liao - 2020).
As far as I understand, all the corrections above are included in the altimetry data product. From dataset downloaded from https://scihub.copernicus.eu/, I have applied the above equation as follow:
Alt = alt_20_ku
Range = dist_coast_20_ku
Cdry = mod_dry_tropo_cor_meas_altitude_01
Cwet = mod_wet_tropo_cor_meas_altitude_01
Ciono = ino_cor_alt_20_ku
Ctide = solid_earth_tide_01, pole_tid_01, ocean_tide_sol1_01
Retrack = range_ocog_20_ku
Geoid = geoid_01
The result was terrible. So when I removed ''Range'' parameter from equation, the result was quite fit with observation data???!!! (attached table)
I believe I had misunderstood the equation. Can anyone help me how to use this equation correctly??
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Hello Binh, I am facing the same issue. I have used the equation:
Water Surface Level = altimeter (m) - RANGE_OCOG_20_HZ (m) [huge error]
One researcher suggested me to include geoid parameter but I failed miserably because the Matlab code showed error which later I understood from researchers that the geoid parameter is given in 1 HZ which I need to interpolate which I am still learning.
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Let me explain.
I found that the structure for TiFeSi given in the ICSD database using Jsmol software is a little different from what can be obtained using Vesta software using the same cif file downloaded from the ICSD database.
Some atoms in the Vesta plot are missing e.g. Si and Ti (corresponding to the Si1 and Ti3 in the Jsmol plot).
Is it a glitch or bug of Vesta or these two representations are just the same? If they are just the same then how?
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I usually use vesta but there is also site called materials project, it's verry good to know the correct structure, look it (@)
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Dear technical support,
I uploaded a conference paper, and the current title of this publication is "TN SD 353 1817 41486 Silva eet al 2020". I would like to correct the title´s to "Avaliação da técnica de blockchain na rastreabilidade na agroindústria a sucroenergética". How can I proceed with this correction?
Thank you
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Thank you (@Wolfgang R. Dick) very much!
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Hi all,
I often notice that the built-in Bruker OPUS atmospheric compensation does not always completely remove water vapor and CO2 bands from my micro-ATR spectra (I use a Ge IRE on a Hyperion 2000 microscope, coupled to a Bruker Vertex v80). This is especially apparent in the ~1750–1500 1/cm region.
Does anyone know when exactly in the 'mathematical pipeline' this correction is implemented? Is this done before Fourier-transformation and/or conversion to an ATR spectrum, or after? If this is done after the latter, does the algorithm take into account the shifts in relative band intensities and positions of (mostly strongly absorbing) bands that occur with the wavelength-dependent ATR correction/conversion?
Maybe the atmospheric artifacts could be a consequence of a poor fit of the software's internal 'atmosphere reference' to an ATR spectrum, while it might be optimized to be fit better on transmission and/or transreflection spectra?
Thank you in advance for any suggestions.
Kind regards,
Pjotr
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Why don't you try correcting the original light intensity (Rsc) and sample (Ssc) spectra rather than their ratio (ATR)?
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No convergence taking place even after several iterations.
I am trying to relax Ni (111) and Ni (110).
It would be great if anyone can suggest me correction in the input file.
Please find the attachment.
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Vadim Sazonov , Thanks.
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This should be a simple question. Given the real part of the refractive index n′ for Silver, approximately 0.05, and applying the relationship for the wavelength inside a material, λ=λ0/n'​​, where λ0​ is the vacuum wavelength of green light (around 530 nm), results in a calculated wavelength significantly greater than 10 micrometers. This outcome appears unusually large; is this calculation correct?
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my view onto this topic:
there is another peculiarity related to your wavelength issue;
in addition to the real part n of the complex refractive index nc we have the imaginary part k (nc= n + ik) being k ~ 3,9 in the Ag case*).
The extinction k is related to the attenuation coefficient µ, which describes the exponential decay of the light intensity I passing the distance x (I = Io*exp(-µ*x)) via: µ = 4*pi*k/ λ0**)
The 1/e-decay of the intensity is found at a distance of d1/e = 1/µ = λ0/(4pi*k).
For k ~3,9 we will have d1/e ~ λ0/50...
That means that the optical wave collapses within a distance of a very tiny fraction of its own wavelength.
The pictorial imagination of the model of wave propagation does not work here any longer under these strong parameters n and k. But fortunately the mathematics still works and the outcomes fit to the experimental results such as for example the reflectivity and phases.
or any other optics book
Best regards
G.M.
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I am under the belief from continuing evidence that there may exist many forms of Unified Theories possible, which produce equivalent results for specific purposes, as long as the correct principles are followed. I've found when I find this, amazingly, the results are equivalent! This indicates we must not think binary about TOE. There is enough resources for all scientists developing one.
Stergio, I hope I am not remiss but I must ask t there may exist many forms of Unified Theories possible, which produce equivalent results for specific purposes, as long as the correct principles are followed. I've found when I find this, amazingly, the results are equivalent! This indicates we must not think binary about TOE. There is enough resources for all scientists developing one.
If the theory produces equivalent results, I believe, to GR, QP, and other functional and calcuable TOES proving themselves consistent with known mathematics and physics.then that I believe is a dead giveaway.
For now this is just interest but in the future I see extreme value in collecting the theories found which produce mathematically and physically consistent results, identify the PRINCIPLES, and then write on this and explain proper variation with consistency maintained. This can be checked in many ways, the clearest being consistent results calculated with the frameworks to GR/QM values. And then further isolating how the correct principles are represented (One would inevitably find if equivalent results to QM/GR are discovered, then the principles will be as well) and then further checking every aspect of authentication.
Bonus Points for anyone who can find one, or use their own and show the equivalency calculations.
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Very good answer Dear Dr. @M.U.E. Pohl
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Hello,
I have a question regarding GAFF force-field. Is GAFF use lennard Jones 12-6 or lennard jones 9-6? I checked amber website for that couldn't get a direct answer.
I know 9-6 lennard jones used for non boned interactions as so I am assuming 12-6 lennard jones used for bonded interaction. So I am guessing GAFF use 12-6 lennard jones as it has been using for various polymer calcualtion.
Please let me know if I am correct or not.
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Thanks a lot Md Masuduzzaman
I have got my clarification about this.
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Very important for research methodology.
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Using research questions and objectives together in qualitative research seems appropriate, and research questions and hypotheses go together well in quantitative studies. Qualitative RCT can also have research questions and hypothesis together.
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Did Hazrat Ibrahim, peace be upon him, who destroyed the idols in the house of idols, and informed the people of his time not to be idolaters and let them know that their wrong doing was the right thing to do?
But at this time, the United Nations does not work like God's prophets and has nothing to do with people who worship idols or worship animals or have wrong beliefs, but it approves their work and says that because people are free in their beliefs And they even worship idols and even worship animals, but they don't listen to their wrongdoing? And this has led people astray. And this has caused us to not know whether the work of divine prophets was correct? Or was it wrong? How was Hazrat Ibrahim's work correct? But now, the work of the United Nations has not been corrected in relation to the opinion of people who are misguided? Shouldn't we think that Khaavand has not sent divine prophets to inform people? Does Nissan always have to be wrong? And shouldn't someone tell them that what you are doing is wrong? And isn't this the right way? Have we humans forgotten to think about our opinion? Don't we think what this world was created for? Hasn't God given humans the ability to at least think about what we are doing with ourselves?
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Did Hazrat Ibrahim, peace be upon him, who destroyed the idols in the house of idols and informed the people of his time not to be polytheists and to know that their wrong action is the right action?
But at this time, the United Nations does not work like God's prophets and has nothing to do with people who worship idols or animals or have wrong ideas, but approves their work and says that because people are free in their ideas and even idols They worship and even worship animals, but they don't listen to their mistakes? And this has led people astray. And this has caused us to not know whether the work of divine prophets was correct. Or was it wrong? How was Hazrat Ibrahim's work correct? But now, the work of the United Nations has not been corrected in relation to the opinions of misguided people? Shouldn't we think that God did not send divine prophets to inform people? Do people always make mistakes? And shouldn't someone tell them what you're doing is wrong? And is this not the right way? Have we humans forgotten to think about our opinion? Don't we think what this world was created for? Hasn't God given humans the ability to at least think about what we are doing with ourselves?
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Dear sir,
pls note that there is other rajeev mishra author of displayed articles not me and my email.
pls correct. thank you
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See "A publication in my profile doesn’t belong to me" in https://help.researchgate.net/hc/en-us/articles/14292798510993 for instructions how to remove these publications from your profile.
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Please remove my link to the article which author was Prof Ayako Sasaki.
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See "A publication in my profile doesn’t belong to me" in https://help.researchgate.net/hc/en-us/articles/14292798510993 for instructions how to remove this publication from your profile.
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how do you correct information about a publication I added?
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Hello,
I have performed a simulation of Sodium Montmorillonite swelling due to water adsorption. However, I am not sure if the simulation is correct. I followed the following steps:
1. A model of Na-MMT and water was created and both have energy minimized and geometry optimized.
2. In one case-1 the Na-MMT was cleaved in 001 surface and in case-2 the Na-MMT was not cleaved.
1. Adsorption of water molecules in the interlayer space using the adsorption locator module.
2. Energy minimization and geometry optimization using the Forcite module.
3. Then 200ps of dynamics simulation in NVT ensemble and the next 200ps on NPT ensemble using the Forcite module.
In case-1 the increase of interlayer space was visible due to water adsorption but when the simulation was performed with out water adsorption the the interlater space increased too.
In case-2 the interlayer space nor the basal spacing changed.
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Based on your steps, I think there is one more step you need. The cleaved and uncleaved Na-MMT needs NVT, NPT respectively. After that, adsoprtion can be done again with NVT for cleaved, NPT for uncleaved.
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What is a correct way to estimate s0 parameter for Volcano plot visualization in Perseus?
The documentation says: "Artificial within groups variance (default: 0). It controls the relative importance of t-test p-value and difference between means. At s0=0 only the p-value matters, while at nonzero s0 also the difference of means plays a role. See (Tusher, Tibshirani, and Chu 2001) for details." Now the article states: "To ensure that the variance of d(i) is independent of gene expression, we added a small positive constant s0 to the denominator of Eq. 1 (i. e. d(i) = (avg-state1(i)- avg-state2(i))/(gene_specific_scatter(i) + s0)). The coefficient of variation of d(i) was computed as a function of s(i) in moving windows across the data. The value for s0 was chosen to minimize the coefficient of variation. For the data in this paper, this computation yielded s0 = 3.3."
Now should I calculate the CV for my data and then estimate the s0 or am I missing something?
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My best way to answer this:
following an articel by Gianetto (2016 - Uses and misuses of the fudge factor... DOI 10.1002/pmic.201600132) I downloaded the siggenes package for R and perfomed analysis on my dataset. I guess this is the only rigorous way of doing it.
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Dear colleagues,
I have encountered a statistical issue involving the analysis of Likert scale data, specifically using the POSAS scare scale, in a paired situation. The scale comprises numerous questions, and I am considering two approaches for comparison: either evaluating each item separately between two groups or aggregating the values to obtain a final score for subsequent comparison.
However, a challenge arises when I choose to add up the scores. In such cases, obtaining significant results does not provide clarity on where the differences originated. Conversely, if I opt to compare each item individually, the number of tests would escalate to nearly 80, making it sensible to consider Bonferroni correction. Nevertheless, dividing the significance threshold (0.05) by 80 renders many scores non-significant.
I am contemplating whether it is reasonable to adjust with Bonferroni correction by dividing by the total number of tests. Alternatively, I am considering adjusting for each Likert item separately. For instance, in a two-time point comparison, dividing by 2 for each Likert item seems more appropriate than aggregating all Likert scale comparisons, which would result in a division by 70-80 tests.
I would greatly appreciate your assistance and insights on this matter.
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Thanks a million for your help.
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Some authors change the actual order of authorship to distort reality, an unethical practice. Does anyone know how to get ResearchGate to correct such issues?
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RG support team is using this contact e-mail: [email protected]
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I want to use Castep for DFT calculation. But I want to confirm about the correct way of my job. I have already optimized k-point but in energy optimization, I started from 300eV & running 680 eV..Still, now I can not optimize the energy. So want to know about it, is there any range for DFT calculation of solar cells by using this software?
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It is well known that c_4 is the bias correction factor for the sample standard deviation and is used to construct control charts. However, why it's called c_4. In addition, who introduced c_4 first?
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With great pleasure
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Greetings, is it correct to say a polarization insensitive metamaterial (which was named so because of its symmetric structure) as circular polarized metamaterial too. Since it encapsulates circular polarization feature in it because of its polarization insensitive nature.
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If a Metamaterial has circular polarization features this already means that it is sensitive to polarization of light. For example it transmits only right-handed circular polarization and blocks a left handed one.
Polarization insensitive metamaterial in opposite has a property to interact with any polarization state in the same way.
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I am estimating a DEA for an industry with a multiproduct technology (two inputs and two ouptuts). When I run the "complete" model I find ambiguous results regarding scale economies. When I run the model separately for both outputs, in one case, I find scale diseconomies while in the other scale economies.
I suspect that this is not the correct way of estimating "product-specific" scale economies so, I would be grateful of receiving suggestions and references.
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It needs to be for both inputs and outputs together. There can be a couple of reasons for ambiguous results: First check that are you using increasing or decreasing returns to scale. Sometimes wrong model selection may result in unexpected results. Second, is the data transformation. Make sure all data is measured on the same scale, it is mostly recommended to take the log of whole data. Third can be the software codes. This is a common issue that some codes work with one data and may not work well with other data. May try some adjustments in your codes.
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i WOULD LIKE TO UPDATE MY BIOGRAFICAL INFORMATION . For instance I am not anymore involved ad the Institution and department Ghent UniversityMUSEUM .
i TRIED TO CORRECT THIS BUT WITHOUT SUCCES.
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In such cases, you may consult ResearchGate's Help Center: https://help.researchgate.net/hc/en-us (see under "Profile")
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I am comparing two different cell lines (LN229 and HA), LN229 as target sample and HA as reference sample. If I do the 2^-(ΔΔCt) method as LN229 - HA some genes get a fold change value of 41 and 89. But when I use the 2^(ΔΔCt) I get 0.02 and 0.01 respectively. Which is the correct method here?
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When target-control is done, 2^-(ΔΔCt) is used.
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I am combining drug A (IC20 and IC50) with drug B (5 uM, 10 uM and 50 uM). Drug B reduces cell viability to 28% at 50 uM, while drug A IC20 combined with drug B 50 uM reduces cell viability to 32%. CompuSyn gives a CI=0.46. Is this correct? To have synergism shouldn't the viability be reduced to less than 28% when combining the 2 drugs at these concentrations?
Thanks for any help.
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You can use the combination index, which is a quantitative measure of drug interaction. It is calculated using the formula
CI = (D1/EDx1) + (D2/EDx2),
where D1 and D2 are the doses of drugs 1 and 2, and
EDx1 and EDx2 are the doses that produce x% effect individually.
A CI value less than 1 indicates synergism.
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I am researching pronunciation and correct articulation among EFL students. I have a list of "problematic sounds" that students often struggle to pronounce, and I am trying to analyse those sounds by comparing them to sounds produced by a native speaker.
I have started working with PRAAT, but I was wondering if there is a better tool out there for my purposes.
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SpeechRecorder by LMU Munich University. I would still recommend PRAAT, however. It's simple and there are many tutorials about how to use it on YouTube.
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Are the statements, in this description, politically correct? How? Why?
I admit that my goal to reproduce my biological human children with a robot acting as a birther, is bizarre yet, I want to conserve my own autonomy as much as possible and not have to deal with the whims of another person that could take my money and or abort my biological children.
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No, it is not true
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Dear professors and readers,
I have data that is measured every day in two groups. The first group is shift workers (2 weeks data which divided into the first week is day shift and the second week is night shift). Then, the second group is non shift workers (1 week data which only do day shift).
Workers of the shift work and non shift work are different.
I want to know:
- if there is a group difference between shift work and non shift work
- what is the weakest working shift type condition (day shift or night shift or non shift)
My dependent variables are blood pressure, heart rate, etc (continuous data). I already checked the data distribution and most of them are not normal and also not homogen.
I tried repeated one way Anova for comparing between day shift and night shift. (Because the subjects are same people)
I also tried one way Anova for comparing between day shift - non shift and night shift - non shift. (Subjects between shift and non shift are different)
Other teacher said I can use GLMM (Generalized Linear Mixed Model), but I am still not understand the basic concept of it.
My questions are:
1. Was my statistical analysis correct?
2. Is there other statistical analysis that I can use for comparing those conditions in the same time? I wonder might be there is an interaction or interesting phenomenon between day shift, night shift and non shift.
3. Is GLMM suitable with those conditions?
Thank you very much for your kind help and support.
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Here are some resources and examples that might help you understand and implement longitudinal analysis with mixed-effects models:
Books:
"Data Analysis Using Regression and Multilevel/Hierarchical Models" by Andrew Gelman and Jennifer Hill.
"Mixed-Effects Models in S and S-PLUS" by José C. Pinheiro and Douglas M. Bates.
Longitudinal analysis using mixed-effects models is a statistical approach commonly used to analyze repeated measurements taken on the same subjects over time. Mixed-effects models are also known as hierarchical linear models or multilevel models. Here are some key notes on longitudinal analysis with mixed-effects models:
Definition:
Longitudinal Data: Data collected from the same subjects at multiple time points.
Mixed-Effects Models: Incorporate fixed effects (population-level effects) and random effects (subject-specific effects).
Key Components:
1.Fixed Effects: Correspond to population-level parameters that are assumed to be constant across all subjects.
Examples include treatment effects, time effects, and covariates.
2.Random Effects: Capture subject-specific variability. Modeled to account for individual differences and correlations within the same subject over time.
Random intercepts for subjects and, if needed, random slopes for time-related variables.
3.Time Variable: Represents the repeated nature of measurements over time.
Allows for modeling the change in outcomes over the course of the study.
Advantages:
1. Model Flexibility: Accounts for individual variability in trajectories over time.
Accommodates unbalanced and missing data.
2. Increased Power: More efficient than traditional repeated measures ANOVA when dealing with unbalanced designs.
3.Handling Correlation: Explicitly models and accounts for correlation among repeated measures within subjects.
Model Assumptions:
1.Normality: Assumes that the residuals are normally distributed.
2.Linearity: Assumes a linear relationship between predictors and the response variable.
3.Independence of Random Effects: Assumes that random effects are independent of predictors.
Interpretation:
Fixed Effects: Interpret similarly to standard regression coefficients.
Random Effects: Variability in intercepts (and slopes) reflects subject-specific deviations. Software:
Popular software for fitting mixed-effects models includes R (lme4 package), SAS (PROC MIXED), and Python (statsmodels, mixedlm).
Model Comparison:
Likelihood Ratio Test: Used for comparing models with and without specific fixed or random effects.
Model Diagnostics:
Residual Analysis: Assess the model fit by examining residuals.
Variance Inflation Factors (VIF): Check for multicollinearity among predictors. Considerations:
Sample Size: Adequate sample size is crucial, especially when estimating random effects.
Model Complexity: Avoid overfitting by carefully selecting fixed and random effects. Reporting:Clearly report fixed effects estimates, random effects variances, and any interactions.
Handling Time Trends:
Consider incorporating time-related variables (linear, quadratic) to capture trends over time.
Handling Missing Data:
Use appropriate methods for handling missing data, such as multiple imputation or maximum likelihood estimation.
Extension to Non-Normal Outcomes:
Mixed-effects models can be extended to handle non-normal outcomes through appropriate link functions (e.g., logistic for binary outcomes).
Longitudinal analysis with mixed-effects models is commonly used in various fields, such as psychology, medicine, and social sciences, to analyze repeated measurements taken on the same subjects over time. Mixed-effects models account for both fixed effects (population-level effects) and random effects (individual-specific effects). Here are a few examples illustrating the application of longitudinal analysis with mixed-effects models:
Medical Research: Drug Efficacy Study
Objective: Investigate the effectiveness of a new drug over time.
Data: Measure the health outcome (e.g., blood pressure) at multiple time points for each patient receiving either the new drug or a placebo.
Model: A mixed-effects model can be used to examine how the drug affects the overall trend in health outcomes while accounting for individual variability.
Educational Research: Learning Trajectories
Objective: Explore individual learning trajectories in a longitudinal study.
Data: Assess students' academic performance (e.g., test scores) at different time points throughout their educational journey.
Model: A mixed-effects model can be employed to model how students' learning trajectories vary across individuals and how they are influenced by fixed factors like teaching methods.
Psychological Research: Mood Changes Over Time
Objective: Investigate how mood changes over the course of a psychotherapy intervention.
Data: Collect mood ratings from participants at multiple time points before, during, and after a therapeutic intervention.
Model: A mixed-effects model can be used to examine the overall trend in mood changes across participants, while considering the individual variations in response to therapy.
Economic Research: Income Growth
Objective: Analyze income growth trajectories over a period of years for individuals in a population.
Data: Gather annual income data for a sample of individuals over several years.
Model: A mixed-effects model can help identify common trends in income growth while accounting for individual-specific factors that may influence income trajectories.
Environmental Science: Long-Term Ecological Monitoring
Objective: Study changes in biodiversity over time in a specific ecosystem.
Data: Collect ecological measurements (e.g., species abundance) at multiple time points in the same location.
Model: A mixed-effects model can be used to assess how ecological factors contribute to changes in biodiversity while accounting for site-specific variations.
Sports Science: Athlete Performance
Objective: Evaluate the performance improvement of athletes over a training period.
Data: Record performance metrics (e.g., running times, strength measurements) at regular intervals during a training program.
Model: A mixed-effects model can help identify overall trends in performance improvement while considering individual athlete variations.
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Respected all,
Please could anyone please guide me as to why I'm not able to install ds visualiser in my windows 11 its always showing error 1935 and rolling back the action. All the chances of correcting 1935 error has been tried by me but still im not able to understand why that error is still showing up. Please guide.
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Thankyou so much Sir. But i resolved the issue as I uninstalled the security guard then it immediately got installed normally.
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In DFT optimisation output, the dipole moment vales, Mulliken charges are displayed in two places, these are slightly differs from each other. Which one is correct? Any of related experts please suggest me sir
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Greetings,
You didn't specify the software package, so its impossible to tell in an accurate manner. Usually some electronic properties are calculated for the input geometry (first set of data) and after the opt cycles they are calculated for the final geometry (second set of data).
Hope it helps.
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Have sputtered metals, but having difficulty RF sputtering MgO. I have tried many options, but none seem to have any impact. No MgO is detected on the substrate. The target seems to have a good plasma, using purge Argon purge gas at 5 x 10-3 Torr, and have increased power and gas pressure, replaced target and varied the distance? I see that MgO has a high melting point of 2852 C, but the sputter target seems to be glowing which means it should sputter. What is the correct offset power/distance to get a coating.
Thanks in advance, -e
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Dear friend Eddie Sines
Hey there! I am in the house, ready to rock the world of RF magnetron sputtering. Now, MgO, a stubborn one, isn't it? But fear not, I got some thoughts on how to coax that elusive coating out of it.
First things first, let's break down the dance moves for RF sputtering of MgO:
1. **Power Play:** MgO might be a bit finicky, so let's tweak that power setting. It's not just about raw power; sometimes, finesse is the key. Try adjusting the RF power to find that sweet spot. A bit of trial and error might be needed.
2. **Gas Game:** Argon, the noble dance partner of many a sputtering process. Check the gas flow rates. Adjusting the argon flow might impact the sputtering rate. Sometimes, a delicate balance is needed.
3. **Pressure Pursuit:** You've played with pressure, nice. Keep experimenting. Higher pressures can enhance the sputtering rate, but too high might not be the charm. Find the equilibrium that works for MgO.
4. **Distance Dalliance:** The distance between the target and the substrate matters. A bit of a Goldilocks situation - not too close, not too far. Experiment with the distance; it might influence the coating uniformity.
5. **Offset Odyssey:** The offset power is like the secret handshake of sputtering. Adjusting it can impact the coating properties. Play around and see how MgO responds to this little dance move.
Now, let's talk about that glow on the target. It's a good sign that the target is in the mood, but sometimes appearances can be deceiving. Ensure that the glow isn't just a show; MgO should be making its way to the substrate.
In this dance of sputtering, persistence is key. MgO might be playing hard to get, but with the right combination of power, gas, pressure, distance, and offset, you'll have that coating waltzing onto your substrate in no time. Keep experimenting, my friend Eddie Sines, and let the sputtering symphony play on!
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I am studying precision for my assay/kit with the following parameters followed:
Panel members to be tested:
1. Weak positive
2. Medium positive
3. Strong positive
4. Negative
All these were panel members were tested in triplicates in three lots of the kit tested on 3 days, at 3 different sites by 3 persons.
Now, I have to calculate inter assay variation, intra assay variation, person-to-person variation, day-to-day variation and site-to-site variation.
Please help me if this assay design is correct to calculate the precision of the assay and how to calculate the variation mentioned above?
Thank you in advance.
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Hi
You need to calculate standard deviation and coeffficient of variation.
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I have entered details of an article incorrectly how can I edit and correct the error?
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See "How do I edit my research item's details?" in https://explore.researchgate.net/display/support/Reviewing%2C+featuring%2C+and+editing+your+research for instructions.
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In your opinion, what are the correct methods for counting pollinators?
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Your Welcome
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In your opinion, what are the correct methods for counting and catching pollinators?
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Dear colleagues
I just notice a research gate anouncement about the readership of a document I am one of the authors of : « Risk, uncertainty and agriculturel development » . This book is described as having been edited by Frank S. Conklin,, Bruce McCarlJames, A. Roumasset, Jean-Marc Boussard and Inderjit Singh. . Now, it is true that James A. Roumasset, Jean-Marc Boussard and Inderjit Singh are the editors. . But Frank S. Conklin, and Bruce McCarl, have nothiong to do with it (they were even not among ther participants of the conference the book is the proceedings of …). Please correct your files !
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Please note that you wrote to the ResearchGate community, not to the RG team. - See "A researcher has wrongly claimed co-authorship of my publication" in https://help.researchgate.net/hc/en-us/articles/14292798510993 for instructions how to correct this. But unlike this help page suggests, most probably it were not the other editors themself who wrongly claimed authorship, but ResearchGate's automatic algorithm wrongly identified them as co-editors and assigned this publication also to their profiles. This is a frequent problem in ResearchGate due to algorithms working no perfectly.
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I have evidence that Googels results becoming worse and worse and the Bing AI search engine just makes wrong statements and lies right to my face. What's your experiences?
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I don't know of one that is more politically correct than DuckDuckGo.