Science topic
Reasoning - Science topic
Explore the latest questions and answers in Reasoning, and find Reasoning experts.
Questions related to Reasoning
I am tryin to simulate the heat distribution in WAAM , GOLDAK Double heat source equation is used. The temperature distribution during experiment I attached K-type thermocouple with the substrate at the distance of 10 mm from deposition but while simulation there is not temperature at the 10 mm . what could be the possible reasons
When I have modified gradient program in HPLC analysis, same sample shows different area response at different RT.
Can it be proven that scientific results reflect the truth? If not, would science have any significance beyond professional reasons?
On January 14th, 'World Logic Day' will be celebrated. In connection with this event, I would like to discuss the purpose and, furthermore, the necessity of the formal aspects of logic, which, even in the 21st century, should remain just one part of logic alongside the theory of argumentation and logical propaedeutics.
In a 3-electrode system for checking the cathode of magnesium-ion batteries, with Ag/AgCl reference electrode and graphite counter electrode, when the charging operation is carried out to achieve 100% SOC, the potential reaches 1.2 V, but this potential is not constant. and gradually reaches 0.23 volts. The question is what is the reason for this phenomenon and how can the potential be kept constant
I am getting gel like constancy and it melts during dying. what might be the reason?
Why does the HOMO-LUMO gap calculated using ground-state DFT differ from the HOMO-LUMO gap and excitation energies obtained through TDDFT? What are the fundamental reasons for these discrepancies?
Kindly help me to understand the behaviour of graphs, Particularly the humps obtained in the dielectric const vs temp graph which shift towad higher temp with increasing frequency. But at the same time, temp vs dielectric loss graph increases monotonically.
(Inset shows the temp vs dielectric loss graph.)
What could be the possible reasons for such a behaviour?
Hello,
I induced D18G TTR in E. Coli with 1mM IPTG and ran this against a non-induced sample on an SDS-PAGE. My results show the same molecular weight for both the induced and non-induced sample (~14kDa). I have been researching the reasons behind this and saw something about E. Coli being leaky, what does this mean? D18G TTR is also expressed in inclusion bodies, does this effect the induction of the protein? I am trying to discuss my results but struggling to find the reason behind this.
Thank you in advance
Hello
When we pattern a mask in a wafer, after exposure we noticed that the length of our patterns in the center of our wafer is thicker in copmarison with edges of it.
What is the reason and the solution.
Thanks for your helps.
Is Artificial Intelligence (AI) going to take the major role in the Peer review ? Do you see the - reviewer fatigue as the reason for this ?
In future AI will take over Human As The Peer Reviewers in the academic and scientific Freternity . What do you think? Please do put your views .
Reviewer Fatigue: A Growing Concern
Reviewer fatigue refers to the physical, emotional, and mental exhaustion experienced by reviewers, particularly in academic and professional settings. This phenomenon occurs when reviewers are overwhelmed with an excessive number of requests to review manuscripts, articles, grant proposals, or other documents.
Causes of Reviewer Fatigue:
- Increasing demand: The rise in submissions to academic journals and conferences has led to a surge in review requests.
- Limited pool of reviewers: The number of qualified reviewers has not kept pace with the growing demand, leading to a heavier burden on individual reviewers.
- Time-consuming process: Reviewing requires a significant investment of time and effort, often taking away from other important tasks and responsibilities.
- Lack of incentives: Reviewers often receive little to no compensation or recognition for their efforts, leading to a sense of undervaluation.
Consequences of Reviewer Fatigue:
- Decreased quality of reviews: Fatigued reviewers may provide less thorough and less accurate feedback, compromising the integrity of the review process.
- Delayed review times: Overwhelmed reviewers may take longer to complete reviews, causing delays in the publication process.
- Reviewer burnout: Prolonged fatigue can lead to reviewer burnout, causing individuals to abandon reviewing altogether.
- Negative impact on research: The diminished quality and timeliness of reviews can hinder the advancement of research and innovation.
Mitigating Reviewer Fatigue:
- Diversify reviewer pools: Expand the pool of reviewers by inviting new experts, early-career researchers, and individuals from diverse backgrounds.
- Implement efficient review processes: Streamline review procedures, use technology to facilitate communication, and set realistic deadlines.
- Recognize and reward reviewers: Offer incentives, such as discounts on publications, conference registrations, or monetary rewards, to acknowledge reviewers' contributions.
- Monitor and manage reviewer workload: Regularly assess reviewer workload and adjust the number of review requests accordingly to prevent overload.
By acknowledging and addressing reviewer fatigue, we can work towards maintaining the integrity and efficiency of the review process, ultimately supporting the advancement of research and innovation.
The Role of AI in Scholarly Review: Augmentation, Not Replacement
While AI has made significant strides in assessing scholarly work, it is unlikely to fully replace human reviewers in the near future. Instead, AI will likely augment the review process, enhancing its efficiency, accuracy, and fairness.
AI's Strengths in Scholarly Review:
- Speed and scalability: AI can process large volumes of manuscripts quickly, freeing human reviewers to focus on higher-level tasks.
- Consistency and accuracy: AI can identify formatting errors, grammatical mistakes, and inconsistencies in citations and references.
- Objectivity and fairness: AI can reduce bias in the review process by evaluating manuscripts based solely on their content and merit.
- Content analysis: AI can analyze manuscript content, identifying trends, patterns, and relationships that may not be immediately apparent to human reviewers.
Limitations of AI in Scholarly Review:
- Contextual understanding: AI may struggle to fully understand the nuances of human language, leading to misinterpretations or oversights.
- Domain expertise: AI may lack the specialized knowledge and expertise required to evaluate manuscripts in specific fields or disciplines.
- Critical thinking and evaluation: AI may not be able to replicate the complex, critical thinking and evaluation that human reviewers bring to the process.
- Ethical considerations: AI may not be able to identify or address ethical concerns, such as plagiarism, fabrication, or conflicts of interest.
Human-AI Collaboration in Scholarly Review:
- Hybrid review models: Combine human and AI evaluation to leverage the strengths of both.
- AI-assisted review tools: Develop tools that assist human reviewers in identifying errors, inconsistencies, and areas of concern.
- AI-powered review analytics: Use AI to analyze review data, identifying trends and patterns that can inform editorial decisions.
By embracing a collaborative approach, where AI augments and supports human reviewers, we can create a more efficient, accurate, and fair scholarly review process.
I have never had an orgasm from intercourse or any other sexual activity with a lover. In my thirties, I consulted a clinical psychologist, who told me that there is nothing wrong with me. In fact, he said I was more liberated than most women he meets. When I talked to other sexual therapists about my experience, they told me that my expectations were too high. So if women cannot expect to ever orgasm with a lover, why do sexologists not promote this information to women in the population?
I am performing nonlinear pushover analysis of RC bridge structure by defining fiber hinges and during analysis it shows, 'maximum number of null steps reached, subsequent results will not be available.'
While Research Interest Score was 252.1 on 24.12.2024, my Research Interest Score dropped to 249.9 on 28.12.2024, despite the increase in my citation count (+5). What could be the reason for this?
I constructed a plasmid containing a coding region with 2 mutation sites (genes for lysine and arginine were replaced to alanine) and transformed into Stellar E. coli cells. Following a 16h-incubation at 37°C, several colonies happened to grow, indicating the successful transformation. I further kept it in 4°C and found several colonies changed into pink-like color in the next day (see the attached pictures). I did the plasmid transformation using stellar cells a lot using wild-type plasmid and such color changes never happen. My questions would be:
1. Do anyone here experience it?
2. What is the possible reason for this?
3. Might it be due to the affect of mutations?
4. What are the reasons for color change of E. coli colonies?
Your comments would be very appreciated. Thank you!
Dear all,
I am currently doing CFA for WHOQOL-BREF measures that has 26 items, 24 items are grouped in 4 categories. factor 1 has 7 items, factor 2 has 6 items, factor 3 has 3 items and last factor has 8 items. item 3,4,26 were reversed coded and my sample size N = 250 after removing outliers(n=19), and found that the four factor structure did not satisfy the GOF index. Specifically, χ2 = 572.10 df = 246, the CFI = .902 and RMSEA= .071, p .001, CMIN/df < 3. AMOS wouldn't run SRMR on my laptop for some reason.
Ive followed guidelines and removed 4 items with loading less than .40, one at a time. and the final results were χ2 = 419.48 df = 202, p sig, the CFI = .932 and RMSEA= .064, p .001, CMIN/df < 3. MI were all < 15. In my opinion, I'm not seeing significant improvement, which is suggesting that four factor model is not a good model for my data. I continued doing CFA for the instrument as one factor model (as found in previous studies) and found similar borderline results.
Currently, i am not sure how to proceed and how to report the findings. And do i still report reliability for the four factor model (there were all satisfactory >.70 before and after removing 4items)?. Can i use the four factor model in my subsequent analyses, like convergent and discriminant validity (non healthy vs healthy group)
if someone could help direct me to a direction or share some input, i would be very grateful. thank you
In studying fractional differential equations (FDEs), I have observed that most research focuses on fractional orders between 0 and 2. However, studies or applications involving FDEs with fractional orders in the range of 2 to 3 or higher appear to be rare.
What are the theoretical or practical reasons for this limitation? Are there any references, applications, or research areas where higher-order FDEs (α>2) have been explored or utilized? I would greatly appreciate any insights, suggestions, or references for further investigation.
so basically, I made 2 samples of graphene oxide using improved hummer method, after washing 1 sample has orange brown color with a PH of 3 after 10 time washing with DI water, the other sample is black color with a PH of 5 after same number of washing, what could be the reason? why my 1st sample's PH is not increasing ?
ChatGPT reveals that while its story begins around 2015, its current capabilities are the result of years of research, development, and most significantly learning from vast amounts of data, per the below.
· GPT-1 – June 2018 (117 million parameters)
· GPT-2 – February 2019 (1.5 billion parameters)
· GPT-3 – June 2020 (175 billion parameters)
· GPT-3.5 – November 2022 (further refinements on GPT-3)
· GPT-4 – March 2023 (multimodal, improved reasoning)
· GPT-4 Turbo – November 2023 (faster, more cost-efficient variant)
Turbo, the last version, is the prime engine processing all queries since its release, both paid and unpaid. This vast amount of data includes the near totality of human savoir-faire, professional and scientific knowledge bases in all fields, to the point that it can pass strict professional exams and write theses at the doctorate level.
The question is: with this humongous amount of data, and their extensive language-based reasoning capabilities, why have we not seen any scientific breakthrough by these LLM’s in nearly 15 years of fending on their part altogether? Does that say something about our model of science (scientific method), and the value and validity of what we know in science, in particular the fundamental premises in all disciplines? Is this a verdict on the quality of what we know in terms of our scientific principles? In light of this null result, can we expect what we know to tell us something in the least amount about or toward the resolution of what we don’t know? If there is a hard breaking between our knowns and the unknowns, can the LLM’s help at all leapfrog the barrier? Given ceiling being currently hit in their learning capacity, would more time make any difference?
I'm currently working on the validation of the test on fluid reasoning in children. I would be grateful to your kind recommendations on the topic.
Hello,
I have performed DSC for my pure pigment sample and pigment mixed with PVA but, there is no peak observed in the graph. Samples were dried well and there was one heating cycle from 30 to 250 degrees. Kindly share your thoughts on the possible reasons for that.
Thank you
The prevalence of autism is on the rise. As an educator, I would like to know why the rates of autism has increased.
Despite the quality of many research papers published in Arabic, they are poorly cited. Is the reason for this due to the level of the journal, the language in which the research was published, or are there other reasons?
FFor reasons that are not worth mentioning, I do not have the funds to buy a copy, nor any way to obtain them.
Hey All!
I am wondering what might be wrong with my band structure. I did the calculations using VASP and plotted the results using Origin. Although I have tried changing various input parameters, I keep getting more or less the same band structure. Can anyone help me identify the problem? What could be the possible reasons for this discontinuity?
Any suggestions or help would be appreciated.
Thank you.
I have done a gram staining for an unknown bacteria. That was confirmed that the bacteria is gram positive. But some of the bacilli did not stained properly in the middle? What could be the reason for that?
my predictions,
1. Cells are in different cell cycle stage
2. that could be spores.
Most school improvement theory's i. E. Cramers-Kyriakides focus on the proportionally dominant role of teacher in boosting learning results.
However students ownership of learning, initiative, respinsibikity and accountability are ignored in these family of models.
The reason is that it is more practical to have teachers as a control input because due to emloyment contracts they ceade sovereinty to the system's hiersarchy. However this is a practical /convenience not an effectiveness theoretical reason so not so valid.
Some publishers only allow authors a limited number of e-prints which soon go, so one has to say 'no' to requests. It seems insensitive to have no option but to decline the request without giving a reason.
I am working on yeast surface display library. After I work with yeasts for a while, I obviously see them at very bad conditions.
If I let the media stand for 1 min, I see cells aggregate very fast, form weird turbid media, and precipitate to the bottom super fast.
I assume it might be because the freezing with DMSO was harmful? But I honestly followed every step from a published protocol, so what could be the reason and what should I do?
I am working on a bifunctional catalyst for the zinc-air battery system. The catalyst is a ferrite and carbon composite. While measuring ORR activity, sometimes I see a peak in the LSV plot. For the same sample from the same dispersion, I did two LSVs. One measurement has a peak; in the other, it is not. What is the probable reason for this kind of behavior? Figure attached. Thanks
The last three times I have tried to thank and author for supplying their papers, I have been unable to say thank you. For some reason now it says that I can only say thank you if the author follows me. Could there be some work around this or a Thank you button, as personally I feel rude if I do not say thank you.
Hello to all,
I am trying to do RAPD PCR with Promega green master mix with parameters 95 : 5min , 95 : 1min, 38 : 1min , 72: 2min with 35 cycles but not getting a very distinct band pattern on 2% GEL. what could be the possible reason for that.
The presence of Brettanomyces VBNC in wine can be a risk for subsequent refermentations once the cause of the stress disappears. For this reason I consider it important that this cell group must be correctly identified and enumerated when reporting the number of viable cells by flow cytometry method.
So, is technically possible to quantify the number of viable but non-culturable cells?
I am getting the following error while running bands.x in quantum espresso
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task # 3
from smallgk : error # 1
Not a group
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what could be the reason????
I'm new to single-molecule localization microscopy. I'm curious about why, in DNA-PAINT or PAINT techniques (for example: jacs.2c11969), people typically use very low concentrations of imagers (below 10 nM or so). Can anyone explain the reasoning behind this? what happen if we increase the concentration of imagers?
The Raman spectra of my carbon dots shows G band and D band. In addition to that a comparatively broader band occurs at 2950 cm-1. Can anyone help you to identify the 3rd band and a plausible reason for that?
1- It is very hard to find peak on UV-vis spectroscopy even changing concentration from 100ppm to 0.01ppm. I repeat several times but unfortunately I did not find. Can any one help me that what will be reason?
2- I change wavelength from 190-800nm. The absorption may be lies either around 220-250nm or 550-600nm. What will be suitable UV-vis adsorption peak?
Have you ever read this article?
Muñoz, Lucio, 2015. Did Adam Smith Miss the Chance to State the Goal and Structure of Sustainability Markets in His Time? If Yes, Which Could Be Some of the Possible Reasons Behind That?, Boletin CEBEM-REDESMA, Año 8, No. 11, November 30, 2015, La Paz, Bolivia.
I want to know the reason why Omega, Shi and Phi Scan are performed.
What reasons could be possible as this is not according to the laws
Kindly asking. Due to the passivation of the alloy, the potential and current of the alloy in ECN monitoring have the same trend of change, resulting in almost no change in Rn value. Is this reasonable?
In reading the introduction of a paper, I expect clear coverage of five essential elements. Unfortunately, many papers fail to address these elements thoroughly. Below is a summary of these five key components.
The introduction of a science-based article sets up the context, rationale, and purpose of the research by including five important key elements:
Background/Context: Introduce the larger subject, with necessary background information to orient the reader to the context of the research. Usually contains a general description of the subject area and its importance, in which the study is situated.
Literature Review: This section introduces previous research on the topic and discusses earlier findings, theories, and possible gaps in knowledge. It is an important section as it outlines what is done and where this new study features in the system.
Problem Statement: This clearly states the specific problem or question that a study is trying to answer. It usually arises from identified gaps or unresolved issues within the literature review, and it forms the basis of the research objectives.
Hypothesis/Objective of Study: After identifying the problem, the paper clearly states the objectives or hypotheses of the research. This section provides what this study is trying to achieve or test and offers a clear target toward which both methodology and analysis are aimed.
Significance of the study: This final element stands for the reasons why the research is important to the contribution in the field of study. It continues to give details on how findings might be put to use or applied, hence giving weight to the importance of the research on other researchers, practitioners, or even policymakers.
Put together, these five elements comprise an introduction that prepares the reader for the explanation of the purpose, approach, and relevance of the research.
Welcome to our Survey on the Rejection Reasons and Submission Process!
This survey is designed to gather valuable insights into the submission and rejection processes in academic journals :
By participating, you will contribute to understanding the most common reasons for article rejections, and help fellow researchers navigate the complex world of academic publishing.
Your responses will directly contribute to identifying the best practices for submitting articles to the right journals and avoiding common pitfalls that lead to rejection. By analyzing the factors that influence acceptance or rejection, we aim to offer useful recommendations to maximize the chances of your manuscript's success.
Benefits:
As a participant, you’ll also receive the final results of this study, which will include valuable insights on journal selection, preparation, and submission strategies. These results could help you target the most suitable journals for your research and avoid unnecessary rejections in the future.
Why?
We believe that sharing this knowledge will empower researchers worldwide, enabling you to make informed decisions about journal submissions and enhance the likelihood of your work being accepted. Your contribution is essential, and by completing this survey, you are not only helping yourself but also helping the academic community as a whole.
Thank you for taking the time to participate – together, we can create a more efficient and supportive publishing environment for everyone!
Is it somehow related to tumour microenvironment or some other reason behind this.
There is no specific range i got from DSC analysis. I searched in many research papers but still didn't get any clue about possible defending reason for crystallization temperature ranges between 250 to 320°C.
It's urgent
I'm trying to do geometry optimization of KAgO3 perovskite material in the material studio using CASTEP by setting cutoff energy 500 ev and various k points 888,999,101010,121212. but every time it fails showing the messages mentioned in the pictures. What is the possible reason and solution for successful optimization?
need an explanation from experts. Thank you.
#Material_studio #Geometry_optimization #Failure
Greetings,
For a long while I’ve been wanting to switch to an electronic lab notebook (ELN) system for our group, but a few years ago I gave it up for two reasons. First, most ELNs were optimized for life sciences, so it would have required a lot of tweaking to get this suitable for our materials physics lab (which also does some chemistry but rather little biology). Second, the wifi in our labs was not reliable, so it simply was not feasible. ;-) Now the wifi in our labs is good enough and I hope to be able to find a good option for an ELN that works for us. But there are MANY platforms for ELN out there, so I would love to hear about other labs’ experiences. Are you doing physics, chemistry and/or materials science and did you try ELNs? Please share your experiences and suggest platforms that work. Thanks!
/Jan
I've always tried to thank people kind enough to share their texts with me.
I'm now told I cannot message someone who doesn't follow me.
This is outside my control. I can follow them, but they may choose ,
for their own reasons, not to follow me.
This shouldn't stop me from being able to thank them.
For unknown reasons I started to notice that after sometimes (0.5-1.0 hr) of operating crossflow filtration system, the flux increases steadily with corresponding decrease of rejection of the monitored ions (SO4 and Cl-). several types of membranes were tested with the same problem including NF270, BW30, NF, NFS, etc.
initially we thought something wrong with the cell so we changed it and used brand new Sterlitech cell. We also thought that some needle like pracipitates may have formed, we cleaned the whole system using 4 % cetric acid by circulation for 30 min then thoughly circulating UPW.
The cell we are using is Sepa CF Med/High Foulant System, 316 SS, 75 Mil with an active area of 140 cm2.
After purifying my GPCR, I found that the protein, which is expected to be around 44 kDa, appears to be less than 40 kDa on SDS-PAGE. What could be the possible reasons for this unexpected lower molecular weight?
After solubilizing a protein isolate in water at pH 7, it was subjected at a sonication treatment in ultrasound bath at 40 kHz durign 10 minutes. After that precipitation was observed.
Which one will you prefer and what are your reasons?
I have a time series data that is stationary. There is no multicollinearity (VIF value is less than 5).
My dependent variable is industrial turnover, and one of my independent variables is export data. There is a positive correlation between exports and industrial production. In simple linear regression, the model is significant, and the regression coefficient is significant and positive. The scatter plot also shows a positive relationship.
Also, the correlation between the export variable and other variables is very low; the highest correlation is 0.6 with imports. Others are less than 0.5.
However, in multiple regression, the regression coefficient is significant but negative. In the Lasso regression model, the coefficient is also negative. What could be the reason for this?"
What is the reason for appearing of peaks below 100 degrees in H2-temperature programmed reduction?
Philosophy
Modern Historical Schools
Qubit gives this error after reading second standard. It asks to read the standards once more or you can close and continue reading the samples but I am not sure if we can use the results. I could not find a detailed explanation in the user manuel. I would be very happy to hear your experience.
Thanks,
Sema
Recently, we monitored the electrical conductance (EC) of a karst spring water. We found EC was increasing with rainfall processes, both during rainfall event and seasonal scale. What are the reasons for this phenomenon? For each reason, what data might be needed to support an opinion?
Hello!
I've been tasked with comparing the DNA quantification abilities of the Qubit Fluorometer and our lab's Filtermax F5 Microplate Reader. We've been using the fluorometer so far but with many samples coming in we're looking to use the microplate reader to speed things up.
I prepared a series of standards using the 10.0 ng/uL standard provided in the Qubit 1X dsDNA HS Assay Kit to a final volume of 210 uL each. The reason for making my own series of standards was to achieve a more accurate calibration curve for samples with lower concentrations. I also prepared three sample tubes with 2 uL of sample and 198 uL of Qubit working solution for a final volume of 200 uL each.
I prepared the samples in microtubes that fit into the fluorometer, read the samples in the fluorometer and then transferred the solution from each tube to a black 96-well plate to be read in the microplate reader. I set the excitation to 485 nm and the emission to 535 nm.
I'll attach a photo of my results. The fluorometer provides its own concentration estimation directly when samples are read. For the microplate reader, I constructed a calibration curve by plotting the fluorescence against the concentration of the standards and then used the equation of the line to estimate the concentrations of the samples. I don't know why the microplate reader is estimating a concentration that is nearly double what the fluorometer estimated?
what are the appropriate solutions to reduce breast cancer?
Hello Scholars,
I am working on a dynamic impact topic and will use the NARDL model for this. Could you give me an idea if this model is suitable for dynamic analysis? If yes, what are the reasons? If not, why not? Thanks
Hello everyone, I have an organic material functionalized with an inorganic material. When performing the FTIR analysis on the functionalized material, a kind of bands appeared in the infrared spectrum between 1000 and 500 cm-1 that were not previously found in the organic material. Could someone explain this to me?
What is the reason for the appearance of new interaction bands that were not previously found in the FTIR analysis? Thank you.
There are many different ways and reasons for learning or not learning.
Are disappointments and traumas a barrier to learning or do they trigger learning?
I reckon that it must be obvious, but I was analyzing XRPD data from different patents and I would like to understand and, if possible, reference suggestions that explain why the variation of 2theta scale is given as 2theta "± 0.2°Θ" (the source and reason for this error/variation). Thank you in advance.
Working with Ag/AgCl reference electrode and platinum as counter electrode.
Hello everyone,
I am encountering an issue with my Caco-2 cell cultures where the TEER values are not increasing and have remained around 40 ohms since day 3 post-seeding. Here's a summary of my protocol and observations:
- Plate Type: Millicell®-24 plates with an active membrane area of 0.7 cm² (1 µm; PET).
- Seeding Density: 60,000 cells/well, as recommended by Millipore.
- Culture Medium: DMEM (high glucose) + 10% FBS + 1% P/S.
- TEER Measurement: Using an older voltohmmeter, which reads slightly below 100 ohms for empty wells (suggesting it is functional).
- Observation: My Caco-2 cells seem to be growing unusually fast. They originally grew in RPMI medium, taking 4 days to reach confluency at a 1:10 split ratio. After switching to DMEM (high glucose), they reach confluency within 3 days, even at a 1:50 split ratio.
I have considered several potential issues:
- Voltohmmeter Condition: Despite being old, it gives reasonable readings for empty plates.
- Seeding Density: Literature suggests a wide range of seeding densities (from 4 x 10^4 to 13 x 10^5 cells/well), which might affect TEER development.
Could the unusually rapid growth rate in DMEM (high glucose) affect the TEER values? Should I adjust the seeding density despite following the recommended protocol? Are there any other factors I might be overlooking that could explain the persistently low TEER values?
Any advice or insights from those with experience in Caco-2 culture and TEER measurements would be greatly appreciated.
Thank you!
#Caco-2 #TEER #Transwell
Why bracket tube, stay tube & 9 ton composite insulators fails in railway OHE system . What are the reasons