Science topic

# DRIFT - Science topic

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Questions related to DRIFT
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Somewhere in the world there must be a bunch of scientists working to establish a more accurate value for the mass of the electron.
NIST publishes an updated value every 5 years, so I assume someone is doing the measuring.
This field is of great interest to me, as my hypothesis predicts a slowly drifting electron mass.
If anyone happens to know someone directly or indirectly, I would love to have a contact.
Richard Lewis said "Can you summarise how you arrived at this result."
Yes, since electric potential is energy per charge one can not simply count the number of electrons and number of protons, this may give you the average charge, but not the average electric potential.
Remember we are talking about E/q and protons have substantially more energy than electrons 938 MeV vs 511 keV so the energy per charge of ground potential is on the order of Fe56 (iron) which makes sense because earth is for the most part iron.
Another way to describe energy per charge is "mass per nucleon" and for Fe56 tis happens to be close to 930 MeV/c^2.
Hydrogens mass per nucleon is 938 MeV/c^2 and as we know there are no elements above Hydrogen in the table of elements, so unless someone comes up with a super element that has a mass per nucleon higher than hydrogen I think it is safe to assume 938 MeV to be the maximum energy per charge ratio in our local universe.
So it seems perfectly reasonable to think of the absolute electric potential scale as going from zero to 938 million volts, where the electron sits at 0.5MV, earth sits at 930 MV and the proton sits at 938MV.
Now do you see why it is so absurd not to consider the observer as having an effect on experiments?
We are literally the elephant 🐘 in the room.
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For example, I have a single mode fibre based Mach-Zehnder interferometer, when I put it into a temperature stablised enviroment, there would be a linear phase drift? What is the phase drift at different temperatures? Is there any paper talking about this?
Fiber-optic temperature sensors operate on the absorption/ transmission properties of gallium arsenide crystal semiconductors. Increases in the crystal's temperature have the effect of shifting its transmission spectrum to higher wavelengths, jumping from essentially 0% to 100% at a specific wavelength.
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Does anyone have insight as to whether it's possible for K-internal to go bad?
We are performing whole-cell patch-clamp recordings. For the past few months we have been having issues with cells dying shortly after forming a gigaohm seal and breaking in. I can only hold a cell for 10 minutes or so. We have checked pipette drift, the pipette isn't drifting. Our slice quality is fantastic. The only other factor we can think of is internal solution. All of our internal is made, dated, placed in hundreds of small containers, and only one or two containers are thawed on the day it's time to patch.
At this point I've patched onto hundreds of neurons with this problem, statistically at least one should have survived past 10 minutes but none have.
Is it possible for K-internal to go bad?
Besides filtering, cheking osmolarity and ion composition of your patch solution, you may try perforation with amphotericin as an option for WCR.
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Apps such as https://chat.openai.com can now collate diverse information in response to a question and compose well phrased readable essays. The are likely to become more capable over time and through better ‘algorithms’ and larger training datasets.
Possible impact areas (more please) :
- ethics
- the process or craft of research
- how academic research is owned and monetised
- the drift of academia‘s attention moving to what the apps best facilitate
In my opinion, I can see the potential impact of AI-powered text generation in those areas. For instance, ChatGPT or other similar AI systems have the potential to revolutionize several areas of society, including the field of research. They can be used to collate and summarize large amounts of information, provide expert advice, and even generate text, making them a powerful tool for researchers. However, there are also other considerations to take into account.
In terms of ethics, there are concerns about the potential for AI-generated text to be used for malicious purposes, such as impersonation or spreading misinformation. The use of AI-generated text also raises questions about authorship and accountability.
The process or craft of research may be impacted by the ease and speed at which AI can generate text, potentially leading to a decrease in the value placed on originality and creativity in research. It may also make it easier for researchers to quickly produce large quantities of text, potentially leading to a decrease in the quality of research.
Academic institution processes may also be impacted. One potential impact is on academic integrity, as the technology may make it easier for students to plagiarize or cheat on assignments. Additionally, these systems may pose a challenge to the detection of plagiarism and academic misconduct, as they are able to generate unique and original text. Educators may need to adapt their methods for detecting and preventing plagiarism and may need to use technology tools to help them identify AI-generated text. Other areas where AI may impact academic institutions include the automation of repetitive tasks and resource management, which can help educators to focus more on teaching and learning.
The ownership and monetization of academic research may also be impacted. In fact, AI-generated text is making it easier for researchers to produce and publish large quantities of research. Therefore, leading to a decrease in the value placed on original research.
Finally, the drift of attention from academia is moving to what AI best facilitates. As AI-generated text becomes more sophisticated, it may become more useful. Specifically, useful for certain types of research, leading to a shift in the focus of academic research.
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Hello,
I have been following the Drift method for my chars (0,1M NaCl solution and pH adjusted with 0,01-0,1M NaOH/HCl) by adding 50mg char in 50mL of a 0,1M NaCl solution pH adjusted.
One of my main problem is that the pH final is always above (except for 11,03 where the pH final was 11) the initial pH. I have been doing th range of 2,5 - 11,3 and I can't find a really big tipping point. What am I doing wrong? Is it my NaCl solution that is too concentrated?
Thanks !
It is possible that the pH of your solution is increasing due to the addition of the char. Char is a porous, carbon-based material that can absorb and release ions, including protons (H+), which can affect the pH of the solution.
One potential cause of the pH increase could be the release of alkaline ions from the char during the drift experiment. It is also possible that the pH increase could be due to the release of CO2 from the char as it reacts with the water.
To determine the cause of the pH increase, it may be helpful to measure the pH of the solution before and after adding the char, as well as the pH of the char itself. It may also be helpful to try using a lower concentration of NaCl in your solution, or to try using a different type of buffer to maintain the pH at a constant value.
It is also important to ensure that you are using accurate and properly calibrated pH measurement equipment, as incorrect pH readings can affect the results of your experiment.
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Dear all,
I have been trying to use ArtRepair and I have some questions regarding the preprocessing I am doing, and I would be very grateful if you could answer some of them. The preprocessing I am doing is as follows:
1. “art_slice”: Normally the threshold has to be modified until it is inferior to 5%.
- IS IT OKAY IF THE THRESHOLDS ARE DIFFERENT FOR DIFFERENT PARTICIPANTS?
- WHAT TO DO IF THE MASK CREATED IS NOT ACCURATE (THERE SEEMS TO BE DATA OUTSIDE THE HEAD)?
2. Slice timing
3. Realign & reslice
(4). art_despike IF “visual inspection of the ArtGlobal figure uncovers greater than +/-1 % drift in the mean global signal across the entire time series”.
- IS THERE A WAY TO CALCULATE THE PERCENTAGE OF THE SIGNAL DRIFT IN ORDER TO CHECK IF IT’S GREATER THAN +/-1 %? (For example by calculating the % of decrease between the maximum and the minimum value OR the first and the last image?
5. Coregistration
6. Segmentation
7. Normalization
8. Smoothing
(9). art_global: apply if art_despike was not applied.
When using art_global, users are asked “always repairs 1st scan of each?”. IF I ALREADY DELETED THE TWO FIRST DUMMY SCANS, SHOULD I REPLY “YES” OR “NO”?
- IF THERE IS TOO MUCH MOTION, IS IT OKAY TO SKIP “art_motionregress” AND USE THE “.rp” FILE FROM THE REALIGMENT STEP AS MOTION REGRESSORS?
- WHEN USING MOTION REGRESSORS, IS IT BETTER TO LEAVE THE SCAN-TO-SCAN MOVEMENT THRESHOLD AT 0.5 mm/TR?
- IS IT A PROBLEM IF ART_DESPIKE IS PERFORMED FOR SOME PARTICIPANTS AND ART_GLOBAL FOR OTHERS?
Finally, I would like to know if you believe the preprocessing I described is correct or not.
I would be extremely grateful if any of you could answer to these questions, it would be very helpful!
Best,
I recently met similar questions and found this post. I was wondering if your questions have been solved.
Thank you!
Best,
Yidian
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Also, when do we use unit root (ADF) with trend and unit root with drift?
Yes, if I(1) is stationary then I(2) will be stationary.
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I need maximum force in every drift in one Composite Shear Wall(CSPSW). I utilized dynamic Explicit and apply cyclic loading . I obtained hysteresis curve of my analysis. But how can I procure backbone curve out of analysis outputs?
Dear Moein,
First of all note that you need to work on the envelope of the hysteresis curves.
Moreover, you require many more than one analyzed case. In fact, backbone curves are generalized force-displacement curves portraying the whole behavior of system from loading initiation until collapse, and should included the material as well as geometrical parameters as variables.
You can use either of numerical (soft computing) or calibrated analytical approaches.
For further information, you can call me whenever you wish.
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Keogram is a analysis technique used in all sky images to demonstrate the E-W and N-S information from the images.
E-W keogram gives the longitudinal offset information of the plasma bubble drift and N-S keogram gives its latitudinal variation in intensity as well as it provides the meridional drifting if any.
We plot this keograms in MATLAB where you get the options as RGB, Grayscale etc. Which option is scientifically correct as far as the all sky imager analysis is concerned?
I use grayscale, but sometimes using RGB option gives complicated plot, in which it is very difficult to track the bubble movement.
Thanks.
Our images are single color images nd it is good to see in grey color. I think gray color keogram is better visualize the events.
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When you speak of damage, is it the apparent cacking, residual, permanent distortions, the roof level drift, or the invisible concrete pulverisation, lap splice failure or rebar slippage or something else?
Damages in the structures are the result of distress due to bending, shear, bond, torsion, fatigue or any such action. The resulting phenomenon will be cracks and deformation which may become so significant that the stricture may not be serviceable. collapse in the structure is with large deformation which may not be recoverable. In fact in limit state design a structure will reach a collapse stage when it will have plastic hinges equal to its indeterminacy plus one that is becomes collapse mechanism (due to static mechanism or kinematic mechanism).
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How can we reduce the breakdown voltage drift of Insulated Gate Bipolar Transistor (IGBT) after 1000 hours of HTRB reliability test? For instance, the BVces dropped from 1590V to 1450V after HTRB.
I think the main part here is mobile ions (Na+) gettering.
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what causes Breakdown voltage (BVces) to drift after HTRB reliability test? I do understand HTRB is an accelerated test which eventually leads to carrier's mobility degradation in the field depletion structure. But what is the main reasion causing BVces to reduce from 650V to 550V after 1000 hours?
is there any recommendation to reduce the decrease the BVces after HTRB test?
Hi Dr Christian Zorn Thank you for your explanation!
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Hi, recently I am trying to correct the baseline drift for the targeted FFA LC-MS method. Our system still use a HPLC so I have to downgrade one of the UPLC method. All the mass are fine, but I see a gradual baseline drift for mass C16:0 (Neg, m/z=255.23) and a suddent uprise of the basline for mass C18:1 (Neg, m/z=281.25).
Currently, the method is setted as following:
Column: Gemini® 5 µm C18 110 Å, LC Column 250 x 2 mm, Ea
Solvent A: 3:2 (v/v) acetonitrile/water containing 10mM ammonium acetate
Solvent B: 1:1 (v/v) acetonitrile/isopropanol (this in origianl method have 10mM ammounium acetate as well)
Gradient is : 1ml/min SolventB 0min, 10%; 1.7min, 10%; 11.9min, 35%; 14.9min, 100%; 17.9min, 10%; 20.0min, 10%. Pressure is highest at 275.4 bar (3994 psi)
I am reading a bit for this fixing, and also for the system limitation. And here is some of the change that I think of that might help me with this.
1. The pump we use is Agilent 1260 G1312B, the pressure range is 0 – 600 bar, 0 – 8700 psi, but my collegue and I keep having problem if we run above 3000psi, so one of the change I am thinking is to reduce the flow rate to 0.6 or 0.8 ml/min
2. I know the ammounium acetate does not dissolve in ACN or Isopropanol, so 100%B in the gradeint is probably bad for the column so I am decreaseing the %B to 95%.
3. The ammonium acetate alone can only be a salt solution and it's not properly buffered. I will try add (0.05% or 0.5%) ammonium hyrdoxide or acetic acid to properly buffer the solution.
These are some of the change that I want to make that from my understanding will be a better practice for the LC run, but I haven't seen clear clue that one of these change will definitely help fix the issue that I am having right now which is baseline drift for paticular mass.
Thus, I am wondering if I miss any points or anyone have similar situation before and how did they fixed it. I also add a figure to show the two
Here is a picture for the situation
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Dear all,
I' m facing some problems with my western blot. The bands of markers seems normal in the gel after electrophoresis, but they drift after transferred to the membrane (showing in the picture)? Does anyone know what could be the reason? I've met this a few times.
Thank you so much!
It looks like something is wrong with your transfer setup. All the marker dyes are being pulled to the same point in the top middle of your gel. Something there acts as a stronger cathode than the rest of the cathode during your transfer. Perhaps the insulation on one of the wires has degraded.
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What is the origin of the shift (up) in the baseline of the UV-VIS spectrum as noticed from 300 nm to 800 nm in the screenshot attached? I'm measuring phenobarbital in 0.2 NaOH against 0.2 NaOH blank. I have tried turning off fluorescent lights, CRT monitors, and capping the cuvette while measuring the sample on my HP 8453 chemstation.
Baseline drift is a common problem in UV-vis spectroscopy - see https://ibsen.com/resources/detector-resources/subtracting-dark-spectra/ for a useful outline of the issue. I am glad that you were able to pinpoint the source of error in your experiment, Zaid Assaf. Increases in dark current (e.g. due to heating) seem to be a frequent offender, though loss of minor absorbing species (e.g. consumption of acid during a reaction) or changes in the solvent environment (e.g. in gradient chromatography) could also contribute.
My advice to William Letter is to read questions carefully before jumping to conclusions regarding the poster's knowledge and experience level. Condescending comments like "This is basic spectrophotometry" are not constructive and may deter other researchers from seeking assistance online. In this instance, you mistook the poster's issue with baseline drift as a misunderstanding of the Beer-Lambert law, despite repeated clarification. I hope that you will take greater care in your future replies.
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Hi,
I'm doing an EEG analysis from a collaborating University so I did not collect the data myself. The few of the recordings show a giant drift/wave across many of the channels which is something I have not come across before (attached is a picture). Does anyone know why this artefact occurred? And is there a way to save the recording or should I discard them?
Data has already been downsampled / filtered
Hi! This artefact may be caused by electrode impedances as was commentted before. Another problem that can cause this artefact is the sweat. To eliminate the artefact in EEG already registered, you can filter the low frequencies. Depending on what you need, the filter can be modified.
Best regards
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Antigenic drift with typical 'ladder-like' phylogeny has been observed with multiple lineages in Influenza(Flu) which makes it more predictable and aids in vaccine development on a yearly basis . With Omicron variant also showing similar ladder like phylogeny with XE variant a hybrid of Omicron BA.1 and BA.2. Is it a good sign for the future implications and predictability?
Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic, millions of human cases have been reported globally (WHO 2020). COVID-19 is caused by the newly emerged severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) (Li et al. 2020). By December 2020, >150 vaccine candidates are under development, and several vaccines have concluded phase III trials and licensed in several countries (Corum et al. 2020). Most of the COVID-19 vaccine candidates are mRNA-, subunit-, or vector-based vaccines encoding the spike (S) protein (Folegatti et al. 2020; Jackson et al. 2020; Mulligan et al. 2020; Zhu et al. 2020), which is the surface protein employed by coronaviruses for binding to and entry into the host cell. Thus, SARS-CoV-2 evolution engendering changes of the S protein can have an impact on long-term usability of COVID-19 vaccines.
Within the viral family Coronaviridae, viruses infecting humans belong to the genera Alpha- and Betacoronavirus. SARS-CoV-2 belongs to the SARS-related coronavirus species within the genus Betacoronavirus (Gorbalenya et al. 2020). All coronaviruses share an unusually long single-stranded RNA genome encompassing 27–32 kb and a similar genomic structure (Su et al. 2016). Error-prone RNA-dependent RNA polymerases (RdRp) of RNA viruses such as SARS-CoV-2 contribute to short generation times and high mutation rates (Domingo 1997; Duffy et al. 2008). However, differently from other RNA viruses, RdRp-driven mutation in coronaviruses is limited by a virus-encoded proofreading protein termed nsp14 (Denison et al. 2011).
Beyond the recently emerged SARS-CoV-2 and MERS-CoV, which emerged in 2012/2013 and causes zoonotic infections predominantly on the Arabian Peninsula, there are four endemic human coronaviruses (HCoV). HCoV-229E and HCoV-OC43 were identified already in the mid-1960s, whereas HCoV-NL63 and HCoV-HKU1 were identified more recently in 2004 and 2005 due to increased screening for HCoV in the aftermath of the SARS epidemic during 2003–2004 (Corman et al. 2018). The endemic HCoV and SARS-CoV-2 share several epidemiological and ecological traits. First, the endemic HCoV are comparable to SARS-CoV-2 in their high transmissibility and worldwide spread (Owusu et al. 2014; Corman et al. 2018; Goes et al. 2020). HCoV cause about 10 per cent of all common colds globally, predominantly during fall and winter seasons, and afford seroprevalence rates of up to 90 per cent already in young children (Corman et al. 2018; Edrige et al. 2020). Second, alike SARS-CoV-2 and many other respiratory viruses, repeated upper respiratory tract infections with HCoV are possible despite prior exposure and detectable systemic immune responses (Callow et al. 1990; Farag et al. 2015), as was exemplified by HCoV-229E re-infection within one year in an experimental infection study in humans (Callow et al. 1990). Third, alike SARS-CoV-2 that has likely evolutionary origins in bats, the endemic HCoV originated from an animal source, including bats, rodents and intermediate hosts (Vijgen et al. 2006; Pfefferle et al. 2009; Huynh et al. 2012; Corman et al. 2015; Jo et al., 2020).
Vaccines against COVID-19 provide a powerful mean to create herd immunity and control the pandemic, albeit long-term efficacy remains to be determined (Krammer 2020). No vaccine has yet been approved against any other HCoV. On the contrary, there are several vaccines against the major respiratory illness influenza, which is likely comparable to COVID-19 in the potential for pandemic spread and disease severity (Petersen et al. 2020). Influenza A viruses (IAV) have high evolutionary rates (Fitch et al. 1991) and evolve into antigenically distinct variants escaping community protective immunity within a few years, a process that is termed antigenic drift and requires evaluation and sometimes exchange of vaccine strains on an annual basis (Carrat and Flahault 2007; Rambaut et al. 2008). Among IAV, the endemic subtype H3N2 exhibits the strongest antigenic drift (Fitch et al. 1991; Bedford et al. 2015), largely influenced by its higher mutation rate (Pauly et al. 2017) and large effective population size (Rambaut et al. 2008). Once sufficient community immune responses against SARS-CoV-2 have been built either by wild-type infection or vaccination, a plausible post-pandemic scenario would be that the future trajectory of SARS-CoV-2 will be reminiscent of endemic HCoV and IAV (Petersen et al. 2020).
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I used two samples, one of pure SiO2 and one of pure Al2O3. For each sample I obtained the corresponding ATR (attenuated total reflection) and DRIFT (diffuse reflection) spectra. The spectra look very different from each other, they seem to be from totally different samples. What can this be due to? For both measurements I used an FTIR spectrum of KBr as Background under the same conditions of each measurement.
Spectrometer: Nicolet™ iS50 FTIR
Spectral range: 4000 – 400 cm-1
Resolution: 4 cm-1
Background and sample scan: 32
Zero filling factor: 2
Apodization function: N-B Stark
Phase correction mode: Mertz
Detector: DTGS ATR
Beam splitter: KBr
Background and sample signal gain: Auto
Mirror velocity: 0,4747 cm/s (ATR), 0,0317 cm/s (DRIFT)
Aperture setting: 100 (ATR), 200 (DRIFT)
Accesory ATR: Smart iTR™ Attenuated Total Reflectance (ATR) Sampling Accessory
Accesory DRIFT: The PrayingMantis™ diffuse reflection accessory (Harrick Scientific Products)
A few more things to clarify what Ms. Krol said. All of which can impact how your spectrum appears.
1. ATR is a surface technique so if there is something on the surface of your powders it will show up more.
2. The shifts you see are too much to be a difference related to the ATR element. You might expect a few wavenumber shift but not hundreds. see Milosevic, M., Internal Reflection and ATR Spectroscopy. John Wiley & Sons, Inc.: 2012. or 1. Harrick, N. J., Internal Reflection Spectroscopy. 1 ed.; Wiley Interscience: 1967; p 327.
3. For ATR you typically do not use something that has no absorbance as the reference. You just use the clean ATR with no sample.
4. In diffuse reflectance the KBr is used as a diluent and the only reason for using it as a background scan is to "match' particle size and packing. Other diffuse reflectors with no spectral contribution could be used.
5. In the spectra of SiO2 the spectrum does not make sense. SiO2 should show a strong Si-O vibration and that occurs at ~1100cm-1 indicating that the ATR is the correct spectrum. Google SiO2 spectrum and you will get a number of correct spectra illustrating this point.
6. Similar comments for Al2O3. Al-O vibrations are at very low frequencies (typically below 500 cm-1)
7. Although the band positions appear to be about right for the ATR spectra, in addition to the poorly rationed phonon band from the diamond, there are peaks in both spectra that should not be there and might indicate contamination somewhere.
8. Finally - the Praying mantis accessory is a pain to align to properly. Although the spectra look real, you might be getting a spectrum of something you don't think you are.
Summary ATR and diffuse reflectance should not look that different if you are doing the experiments properly. You will see slight peak shifts and slight intensity variations if you have ATR corrected, plotted the diffuse reflectance as KM units etc. I would very strongly recommend going back and starting again.
• Clean everything.
• Align everything
• Check library spectra to make sure you are getting what is expected.
On the Pike Technologies website (www.piketech.com) you can find a number of resources to understand where you might have gone wrong.
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My group is considering getting a new oxygen sensor for peatland soils and soils under thawing permafrost conditions. Our current sensor (Pyroscience) works well in water and in air, but has issues in a soil matrix (the value needs a long time to stabilise and starts drifting off soon after). Plan is to use it for measurements during the field work, no long time observation (for now) necessary. I appreciate any experience shared and/or recommendations.
Please refer the paper mentioned below which will give you the latest information:
Levintal, Elad, Yonatan Ganot, Gail Taylor, Peter Freer-Smith, Kosana Suvocarev, and Helen E. Dahlke. "An underground, wireless, open-source, low-cost system for monitoring oxygen, temperature, and soil moisture." SOIL 8, no. 1 (2022): 85-97.
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How one can learn independently Simulations like drift and diffusion modelling and many other relevant simulations .
Maybe TOXCHEM model may be of use to you
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I have been performing experiments in which I weigh polystyrene or polyurethane in an analytical balance, but anytime I place my sample, the weight keeps going down and does not stop. I read that probably is a problem with the static of the sample. Has anyone encountered this problem and knows how to deal with it?
Thank you
If you are having a problem with static (which sounds likely given the materials you mention) I highly recommend using an anti-static gun, they are commonly used in analytical chemistry labs. It helps a lot when you are weighing very small amounts or polymers that build up charge easily.
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Now a days because of non availability of labour the usage of pre & post emergence herbicides is more among the farmers. But sometimes due to the herbicidal drift most of the farmers are facing the problem of tip drying, crinkling and sometimes completely drying of the plants. Can anyone please suggest the best management methods to recover the plants from herbicidal drift.
The solution is to spray when the wind is still, increase the volume of the spray solution and use the shield around the nozzle and bring it closer to the surface of the soil.
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Hello,
I have a one cycle of hysteretic curve which has so much less width that it doesn't look like a cycle as it just looks like a line. I want to find area of that loop. I have tried to find the area in origin-lab using various techniques and it comes to be 4 approximately. I just want to confirm that whether this area calculation in correct or not. Please, anybody that have used origin-lab and can find the area between the loop easily, confirm it. Excel sheet is also attached with drift on X-axis and Base shear on Y-axis. P.S base shear is in units of pounds (lbs) and drift has no units then what would be the unit of this calculated area?
Thank you
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Genetic analysis of the COVID-19 virus shows that it is very similar to a coronavirus in bats but the receptor binding looks like the receptor for SARS. This could happen naturally with slow changes of one in ten thousand sequences each year. This appeared all at once. This gives support to the belief that the Wuhan lab took the bat virus and attached the SARS receptor. So, does the COVID-19 show antigenic shift and drift?
Antigenic drift refers to the accumulation of genetic mutations that cause an alteration in the surface of the virus. This is one of the main reasons why a novel flu vaccine is required every year. Antigenic shift occurs when segments from the genome of two different viruses combine to make a novel strain. Coronaviruses are not prone to undergo antigenic drift or shift
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Hi dear friends, Would you please guide me through calculating the wind-drift according to CSA load combinations? That is to say, What are the load combinations shall be used to obtain wind drift? thanks for your time in advance, mohamad
kindly see:
Structural Commentaries (User’s Guide – NBC 2015: Part 4 of Division B) (canada.ca)
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Hello everyone!
I'm trying to replicate analysis 1.3 from the paper: "Phylogenetic analysis of a new morphological dataset elucidates the evolutionary history of Crocodylia and resolves the long-standing gharial problem" of J.P.Rio and P.D.Mannion. With their supplementary files "Raw data: TNT file with continuous and discrete morphological characters (used in Analysis 1 and 3)." and the following protocol :
piwe=
open the matrix
piwe=12 ; (weight of 12)
xpiwe= ; (active EIW)
piwe; (see if all is ok weight of 12 and EIW ON)
Then NewTechnologySearch with :
- on letf side : Sect Search + Ratchet + Drift + Tree fusing (on default setting)
- on right side : Driven search with init addseqs of 5 + Stabilize consensus 5 times with 75 factor
Random seed of 1 and Auto-constrain and replace existing trees ON
Then TBR with Tree on ram.
But I get a tree with the best score of 8900 something whereas in the paper the best score is 8181.9.
Does someone have an idea where I mistaken?
Hi Jonathan, it is quite difficult to determine which is the cause of the difference in score by just reading the commands you used. I think that you should try to contact with the authors.
best,
Santiago
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I have a Steel structure that It has three axes in the x-direction and y-direction. I enter displacement load the head of each column, and I push with 8% drift. When I turn on Nlgeom in step, my chart( force-displacement) does not have nonlinear steel behavior, and in the plastic region, Many forces develop in my chart. It causes my columns to be plastic, but I do not turn on Nlgeom, the nonlinear steel behavior is good, but I do not see local buckling in my beams.
What is the cause?
Dear Farshid,
It is very important to observe the local buckling in the model of the type of analysis and meshing. Therefore, select the type of analysis, RIKS analysis, and create a initial imperfection in the model. Also use the shell element (S4R) for meshing.
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Could someone give me an indication of drift limits provided if any for in-plane flexural or shear failure of URM piers in NZSEE/Seismic Assessment of Unreinforced Masonry Buildings Section C8 ?
The NZSEE document has been effectively superseded by the new Technical Guidelines for Engineering Assessments, which Stelios has provided the link to (also available here http://www.eq-assess.org.nz/).
Some further useful information may be available here:
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Hi,
I acquired multiple confocal stack images of olfactory epithelium from rostral to caudal position from 1 slide. I want to create 3d reconstruction by adding all the z stacks to look at expression pattern of few neuronal markers. I am able to add multiple stacks by selecting "add slice" option. However, there is a distance of 50 micron between every 2 slices. 2 questions:
1) Can I add blank space of 50 micron between every 2 slices?
2) How to align for x-y drift between different z stacks?
Thank you
Raghu
Cheers.
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Citing Surendra Adhikari at NASA, I would like to ask how it is possible to claim that the North Pole drift is caused by climate change:
"Climate change does not only cause the rise of the oceans, it also disturbs the magnetic field of the Earth. "There has been a dramatic change in the direction of pole drift, undoubtedly caused by climate change, which is linked to the disappearance of the ice sheets,  especially in Greenland," said Surendra Adhikari, researcher at the NASA. The North Pole has lost 278 gigatonnes of ice since the beginning of the third millennium.  As a result, the magnetic north pole moves eastward, and faster than before. The melting of ice would account for 66% in the acceleration of the phenomenon."
The magnetic pole drift is caused by the magnetic field strength of the North American flux lobe and the Siberian flux lobe (Ref: 1, 2, Figure 1). This is also based on a comparison with the magnetic South Pole in Antarctica, which is immobile and entirely surrounded by ocean, while the magnetic North Pole is driven by continental mineral density of the two major continents forming large magnetic fields. These mineral densities of the Siberian and Canadian regions are fluctuating with the activity of the internal core and the rotation of the iron core of the earth, seismic activity and change in mineral composition of the mantel over several years. The geomagnetic properties of these region can change drastically by the alterations of the electromagnetic field of the planet Earth, which is also affected by the electromagnetic field of the Sun. How can NASA claim that the North pole ice, which is virtually the same as water around Antarctica in magnitude of electromagnetic strength, alter the position of the magnetic North Pole?
References.
1. Gubbins, David, and Peter Kelly. "Persistent patterns in the geomagnetic field over the past 2.5 Myr." Nature 365.6449 (1993): 829.
2. St-Onge, Guillaume, and Joseph S. Stoner. "Paleomagnetism near the north magnetic pole: a unique vantage point for understanding the dynamics of the geomagnetic field and its secular variations." Oceanography 24.3 (2011): 42-50.
Thanks for this reply. This confirms that the theory of NASA is not fully in accord with geomagnetism.
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I have seen an example of tracking position in one dimension using an alpha beta filter, and I have a similar problem in a different field. In the example the position is first updated via dead reckoning: New position = old position+ velocity times delta t. Then the new measurement is used to update both the position estimate and the velocity estimate using the alpha and beta weights. I would like to see this problem formulated using a Kalman filter. I think I can come up with the variance estimates required and prefer this to somewhat arbitrarily selecting alpha and beta weights. The change in velocity is a drift, i.e. not driven by any known input.
These links might be useful, have a look:
Kind Regards
Qamar Ul Islam
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I have an ICP-MS measuring metals in drinking water. Dissolved Ca precipitates on the cones and causes a decrease in instrument response quickly over time. For example, only 10 samples of high-Ca water will cause a 15% decrease in instrument response. I can follow the decrease in response by running check standards every 10 samples. Is there a way to re-calibrate the slope (or 'reslope') every 10 samples by re-measuring only one standard solution, instead of re-calibrating (10 cal standards) every 10 samples? Or is there another way to correct for drift?
Philip Larese-Casanova Drift correction procedures are the ones i have shared the links here with and am sure you will like them and connect them as well
In this Link you can see that the procedure is introduced that can mitigate the deleterious effect of low-frequency noisesoften termed driftson the precision of an analytical experiment.
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I use a mechanical translation stage with a retroreflecting mirror as a delay line (fs laser - gate(pump)). Despite the retroreflecting mirror ensures getting parallel beams (in & out beams), I noticed a laser beam drift when I scan the translation stage over relatively long distance, i.e. approximately 100 mm back or forth from the mid-point.
I know this can cause troubles for my experiments, particularly I use collinear geometry for pump(gate)-probe experiment, hence both beams must coincide without deviation upon scanning the delay line.
Can any one please tell me, how can I correct that ?
Hi Amr, I agree with the others. And sometimes, I find it is very practical to visualize the two spots (fixed and delay lines) with a camera at a distance - the further it is located from the fixed and delay arms, the better you see the mis-alignement. This simple camera system is very handy for your alignment.
Good luck there
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We are seeing our QC check standard for nitrogen decreasing significantly after batches of 20 runs. The first check is 98 ppm, the next 82 ppm, the next is 70 ppm, the next is 51 ppm and the last one was 34 ppm.
Wondering why the check is slowly being decreased. Is there a way to adjust something in the instrument? thanks.
Best wishes
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I would like to learn how to choose the L and C values in a DSRD based pulse generator circuit. What modeling software can help me do that and determine the waveforms as functions of the L and Cs? In other words, in Figure 3 of the article "4H-SiC Drift Step Recovery Diode with Super Junction for Hard Recovery" by Xiaoxue Yan , Lin Liang *, Xinyuan Huang, Heqing Zhong and Zewei Yang in Materials 2021, 14, 684 they show the L and C values. SInce I am a novice in pulse generation, can anybody please point to any article that discusses how the circuit would be impacted with different values of C and L? Thank you so much.
sorry, I don't know any articles discussing the effect of a variation of the Cs and Ls. A short discussion of the processes in the circuit can be found in Ref. 26 of the article you mentioned but without explanation of the choice of the actual values.
If I understand correctly, you are not interested in modifications of the DSRD but in the circuit. Therefore, a simulator based on SPICE parameters would be sufficient. But seemingly no one has published satisfactory SPICE parameters for DSRDs (possibly, it's due to inherent limitations of SPICE models).
Hence, the usual approach seems to be to model the physical structure of the DSRD by software like Synopsys "Sentaurus" device, and to simulate the circuit in a mixed mode using additionally a SPICE solver. A short description can be found here:
If you don't have access to similar software, if your budget is limited but your time is not (so much), and since the circuit consists of only 10 elements, I guess a viable solution is to write your own circuit simulator (based on simple laws and short time steps), using ideal Rs, Cs, and Ls, replacing the MOSFET by an ideal switch, and modeling the DSRD according to the literature. Once your results for the original circuit look like the published ones, you can start varying the elements.
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Hi guys,
We have been doing single molecule TIRF experiments with virus protein Gag to look into its assembly process. When analyzing the data, some traces look nice, but some have this baseline drifting problem. We tried some optimizations but the problem is still there. We have problems in:
1) as shown in Fig 1 attached, we think there is a clear baseline drifting (signal gradually decreasing around 0 intensity), and
2) in some of the slides, the overall signal is very intense for the first couple of seconds (Fig 2 attached), and then the image gradually become more "normal" (Fig 3 attached). This has been making our data processing process very difficult, and we are not sure if this is also related to the baseline drifting problem.
The buffer we are using contains 100 uM propyl gallate, 2 mM DTT and 4.5 mM trolox. We are kind of new in single molecule TIRF, and would really value expert opinions in how to improve/optimize the system.
If I understand, you are saying there is general background signal that is slowly bleaching? I've encountered fluorescence in medium that bleaches with illumination (and then recovers due to diffusion). Riboflavin is one culprit that is in culture medium and is fluorescent. I was told it can even stick to glass.
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The zero drift can be seen in the attached files.
Hello Qun Zhou ,
I guess you have Zero Check switched on.
A possibility to circumscribe the cause of the drift is to use the preamp out signal available at the rear panel (see page 11-12 of the manual): With External Feedback disabled, you could measure the preamp out signal and see if it is drifting. If not, the cause has to be located behind the preamp.
If the preamp is drifting, you could enable the External Feedback, and use a simple resistor in the external feedback loop. If the drifting disappears something might be wrong with the internal feedback.
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Why Moment Resisting Frame Drift is more than Shear Wall Frame Drift, if they are in the same Seismic zone and the same quantity of material?
• Analyzing two Models ( Moment Resisting Frame and Shear Wall Frame) by Etabs.
• The same property and the same quantity of materials.
• Analyzing both Models in the same Seismic Zones.
• Both Models are the same geometry, the same height and Floors.
My question is:
Why Base Shear and Drift in Model of Moment resisting frame provided more than in Shear Wall Frame?
Due to the difference in the response modification factor, the base shear of both structures will not be the same.
Moment-resisting frames are more flexible than the shear wall; don't you think this is one of the reasons for the difference in the amount of allowable drift in these two systems?
Also, drift computations include the fundamental period, scaling modal drift obtained from modal response spectrum analysis, the seismic design base shear, torsional irregularities in structures, and the significance of P-delta effects.
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I am looking for brain vessel image correction. I do video recording in slices of capillaries and I have some xyz drifts. Is anyone know movement correction solution preferably in imageJ
I am new in plugins use. I found Manual_Drift_Correction-1.0.0.jar.zip plugin and install it but when I trying to start it I got error: plugin or class not found and (java.lang not found.
Thank you in forward
Ivan
There are a couple plugins, StackReg and TurboReg that should help. Just google it and you can find the files to download and install. They used to come with the Fiji version of imageJ, but looks like you have to get them manually now.
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What is thermal drift and what are its causes ? I did nanoindentation of a polymer nanocomposite. To know the thermal drift, at the end of unloading, low load of 0.01 mN was held constant for 70 seconds. There was not any pattern, the depth increased and decreased and at the end the depth was same as it was in the beginning. How to correct for thermal drift in such a case ? If there was only increase or decrease, i could have fit a line or curve to it and correct the displacement readings accordingly. But since there is no any pattern to it what shall I do ?
Thermal drift is used to define any evolution of the displacement of the tip while maintaining a constant force. Of course, for time dependent materials, such as polymers, it can be tricky to separate the effect of creep from the effect of thermal drifts (that are cause by slight local temperature changes). But if you have signifiant displacements (for a material with a very low stiffness for example), then the thermal drift shall be not be a problem.
It is usually better to measure this thermal drift before the test by maintaining a very low load for a given amount of time. A drift rate can then be evaluated and used to extrapolate the thermal drift during the test. The drift free displacement can then be evaluated after the test is over (your software may perform that correction automatically).
The thermal drift shall be evaluated prior to any measurement as it may vary from one test to another. It is very dependent on your device, your testing conditions, your material, etc. And last be not least, the shorter the test, the better it is (regarding thermal drifts issues).
In your case, if you do not have any trend, then you should not be influenced by thermal drifts. You may check that by performing your drift evaluation prior to your test.
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When I'm doing my indentation experiments I choose the central point on the virus to be indented but when the process ends, the force-distance curve does not represent the central point that I chose. I try to manage the image size or sonde velocity but it doesn't work very well.
Dear Yeraldinne Carrasco
Occasionally drifting occurring while performing the analysis it is inevitable to avoid for that you can have a reference given below this might clear your query
Real-time drift measurement for colloidal probe atomic force microscope: a visual sensing approach
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Does anybody have experience how to measure the point of zero charge of buffering materials (e.g., Mn oxides, zeolites, etc. in our case)? The common pH drift method is giving us very weird results, as the materials are strongly buffering the pH to their natural pH. E.g., birnessite, whose pHzpc should be according to the literature between 2 and 4, results in pHzcp of almost 10 when measured by the pH drift method, the similar case with zeolites....Also potentiometric titrations are giving us these highly alkaline values close to the natural pH of the materials....
Don´t you have a recommendation for any other method suitable for this type of materials?
Thank you very much.
I have estimated pHzpc of birnessite (found 2.4), pyrolusite (7.1), hausmannite (6.4), and manganite ( 8.1) using zeta potential measurements and got reasonable results. You can follow this method.
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I've been using the SFI MVLEM element in OpenSees. I conducted cyclic analyses on 3 different experimental walls to verify the response from SFI MVLEM before conducting analysis on a 10 story RC wall building. I successfully verified the experimental response (global as well as local response) of those walls using SFI MVLEM. While conducting the analysis on a 10 story RC Wall building, I noticed that convergence fails at a very small drift of 0.5%, even with different displacement step sizes to conduct the analysis.
Any guidance on troubleshooting the early convergence failure of the analysis using SFI MVLEM would be a great help.
Hello
use Krylov-Newton Algorithm as algorithm and Total Relative Norm Displacement Increment Test for test command
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How to measure an optics thermal drift error in a laser measurement system(Renishaw XL80)?
Please tell me about optics thermal drift and what is the source for optics thermal drift. And How to find the value of optics thermal drift. And how to reduce it?
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Numerical models have been used to explore potential long range predictivity
of coupled models using observed data. The early experiments have been frustrated
by rapid ocean model drift away from the observed state. Do your higher resolution models have the same behavior
The rapid divergence of high resolution models from the actual state of the system is very well known and can be explained by the rapid error growth observed mainly for a fine scale part of the spectrum. The relative behavior of the error for the coarse and fine scales was described by Lorenz in his well known presentation on predictability.
The summary using Lorenz's original wording is as follows:
“1.Small errors in the coarser structure of the weather pattern – those features which are readily resolved by conventional observing networks – tend to double in about three days”
“2. Small errors in the finer structure – e.g., the positions of individual clouds – tend to grow much more rapidly, doubling in hours or less”.
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I tried to perform a spectral matching in frequency domain . I have attached the result herewith. There seems to be a lot of drift in displacement and velocity plot for the matched ground motion. A total of 10 iteration was performed to obtain the match. Can somebody explain the reason and verify my work here ? Also, what is the permissible limit for the drift allowed ?
The ground motion used here is imperial Valley.
Matthew Mabey, the output I obtained was based on 10 number of iterations. The perfect matching at the beginning is because I have used a time step of 0.05 for the natural period of structure. Because my solution of response spectra became erroneous at lesser period. However I am again trying to draw response spectra following the Newmark average acceleration method which is stable for any time step. In mean time I just wanted to know how do we correct the drift in velocity and displacement which is imminent due to the spectral matching procedure ???
Thanks.
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I need to plot normal stress v/s lateral drift. So in ANSYS, is there any option to obtain stresses for selected objects only? If so, please elaborate.
Hey Sneha,
Yes, you can get the stress on the selected body. But, to select that specific part, first you have to split the part during modeling. For example: If you are using Solidworks, there is an option to split the structure into different parts.
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I want to calculate the the time evolution of drift velocity of a particular ion under different range of external electric field in LAMMPS. What would be the command for the same?
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Please suggest for computer based system for processing of raw gyroscope data which method is more suitable for bias drift and noise removal from gyroscope? I need angular velocity in my application.
Improving the Targets’ Trajectories Estimated by an Automotive RADAR Sensor Using Polynomial Fitting
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I'm trying to setup a simulation that tracks particles from a spray nozzle mounted under a propeller blade. I need suggestion on how to setup this simulation in fluent.
look at the manual for particle trackimg
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I'm regressing households' spending (PCE) on disposable income (PDI) between 1980 and 2018 for the U.S economy. I noticed that the coefficient of PDI is higher than 1. I first think that coeff. of PDI may be extreme due to possible autocorrelation or non-stationarity.
While conducting the ADF test, I tried the random walk, drift, and a trend.
However, according to the results of the test, PCE and PDI series are stationary with a drift.
I also applied the Gregory-Hansen cointegration test and find out that series are cointegrated in the long run at the breakpoint.
How can I solve this problem?
@Defne - Do u think that your data has trend or drift? First, ensure it.
If you think that it has drift, only then go ahead with this result otherwise test stationarity without drift. If you find the series I(1) then go ahead with cointegration.
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I observed a decrease in intensity in 4000 QTRAP (AB Sciex) mass spectrometer. It looked like a case of contamination. The standard cleaning procedure did not help. Calibration standard solutions gave peaks of very low intensities. The drift test didn't prove any contamination. Changing the detector voltage also did not help. The service checked electronics and said that it is not the reason of the problem. They suggest cleaning the quadrupoles now. Do you have any possible solutions to my problem or any suggestions?
We had similar problem years ago, ended up being a vacuum leak. check ultimate vacuum, our rough vacuum was leaking slightly difficult to detect. and the instrument could not compensate. new rough pump and fittings fixed the problem.
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can anyone tell me in IDA analysis, increases the scale factor of ground motion from 0.1g and upto 5g. Why the drift ratio vs spectral acceleration curve show linear , even maximum hinges show collapse point.
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As it is known there is a magnetic field in large scale universe, so the particle undergoes a magnetic field will be different in case of expanding universe or static one as it will be in the trivial case; For example the drift of charged particle where it tends to spiral around a field line in this case what is the effect of the large scale on particle drift in a magnetic field
Not sure if this would help or perhaps you know this already:
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When i plot the modal pushover analysis of nonlinear fixed structure, it plotted well, but when i did same for base isolated structure, it says crossed the limit state in first few steps, what might be the reason? Can anyone explain it to me, please?
Dear Nirmala
Generally, the capacity curve in the first mode of the base isolated structure is bilinear that consists of a large elastic part and a small plastic part, because the first mode represents the isolation system.
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I have a question regarding the convergence problems of cyclic (quasi-static) loading for reinforced concrete slab-column connection. Is there any of you have this kind of convergence problem? I have run exactly the same model for the monotonic lateral loading and it was totally fine and gave an adequate result. However, when I change the load into cyclic then it start to diverge even for a very low drift level. I have checked all of the boundary condition and it seems totally fine.
@Sharma, I agree with Dr. Sharma that time step influence the convergence in problems involving time such as seismic forces, explosive loading etc.
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I have a question regarding the convergence problems of cyclic (quasi-static) loading for reinforced concrete slab-column connection. Is there any of you have this kind of convergence problem? I have run exactly the same model for the monotonic lateral loading and it was totally fine and gave an adequate result. However, when I change the load into cyclic then it start to diverge even for a very low drift level. I have checked all of the boundary condition and it seems totally fine.
My question is, can you descibe what factor that may influence this convergence problem? for example, because I am using plastic compression model combined with tensile fracturing, I guess there is an issue after the concrete cracks and it start to soften in an exponential way. Do you think this kind of negative stiffness during the softening may contribute to the problem? Any suggestion and discussion will be so much appreciated.
Best regards,
Andri Setiawan
dear Andri , did u find the issue
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What is the reason for baseline drift of in-situ high temperature XRD pattern at relatively high temperature? Cu K(alpha) radiation was used for the in-situ high temperature XRD measurement of high purity pyrite. The baseline is straight at the temperature below 600°C, while it shifts from down to top as angle increases.
Gerhard Martens Yes, you are right! The diffraction peak of pyrrhotite (Fe1-xS) can be found in the XRD pattern at temperature above 550°C. Interestingly, the baseline begins to shift from down to top as angle increases at the same temperatuer.
The heating rate is 10°C/min at the temperature range of 0~500°C and 700~900°C, while it is reduced to 5°C/min for the stage of 500~700°C. The soaking time is 2 hours for each temperature point.
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I am running an analysis that has six compounds that are evaluated for precision, linearity and drift. I have the unusual problem that drift for 5 of the compounds after analysis is ~ 20% higher, but drift for one compound, TOTM, is doubled, with a drift of 100% or more. I am using Acenaphthene-d10 as the internal standard, and response of this compound is really steady, but especially after samples are injected, the response of TOTM increases significantly. I've been working on this project for about a month, and if I look back at older data, the response of TOTM has been slowly increasing through each analysis, while the response of the internal standard has remained relatively constant. (TOTM initial response was ~ 100,000 - but now it is close to 2 million).
Some of our thoughts for the source of this problem are:
That there are active sites (or something) in the column that is causing TOTM to hang up- running the sample injections pushes that out so that more TOTM elutes in later injections.
That there is a matrix effect from the sample that increases the response from TOTM.
That the inlet is discriminating against TOTM, but then less later on? (I'm running the same method the whole time.)
Other typical players in GCMS methods are the source, the inlet, and the column, but it's still hard to see how any of those would lead to increased response from mostly just one compound.
Any thoughts? Thanks!
I think the answer lies on the boiling point of TOTM. In my opinion, incomplete volatilization of the compound is happening, and your sample matrix acts as a better solvent than pure methylene chloride. I've seen this before with some pesticides and I had to modify the injection mode (from splitless to PTV) and/or using analyte protectants or doing matrix-matched calibration. Here are some of my suggestions:
-Try a split method with a ratio of 10:1; as you know, splitless injections tend to get the inlet dirty and your analyte is very likely behaving as a heavy matrix component. This will also enable you to set a higher inlet temperature in order to enhance analyte volatilization. If you think your samples are dirty and you can get enough sensitivity, I'd change to this injection mode.
-Test some other solvent like DMSO, to see if this solvent can clean the inlet more effectively. If you use DMSO as your injection solvent, be sure to use an adequate solvent delay time, since that solvent can give a very broad peak. Also, make sure your early eluting analytes aren't lost. Be careful of its expansion volume, make sure your liner volume can hold the sample gas volume; because of this, again, a split injection can be helpful, PTV can work too.
-Setting a higher ion source temperature would help you maintaining the ion source clean, but this parameter surely isn't the cause of your increased response. 150 C is indeed a very low temperature, I wouldn't work with such value unless I was interested in some specific ions, but then the samples should be very clean. It is a good idea though, to increase the ion source temperature, due to the high boiling point of your analyte and if you think your samples are dirty. You can also increase the transfer line temperature for a more stable response due to improvements in peak shape.
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Dear All,
We are looking for drift velocity vs electric field of electrons and holes for finding the drift velocity saturation in the amorphous and micro-crystalline silicon.
Please guide me for the same.
Thanks,
Dear Syed,
I think the drift velocity defines the response of the mobile charge carriers to the electric field provided that they are free to move and wander in the material because of the thermal energy. It is said the particles are free. This happens if the material is crystalline.
If the material is amorphous the charge carriers are lying in shallow potential wells meaning they are not free to move in long ranges. At first one applies the field till they come out of the wells and become free. Therefore appreciable mobility is measured first after crossing the mobility gap.
After the mobility gap the amorphous material behave like the crystalline materials. Under this case bone can speak from saturation velocity.
As for the micrcrystalline materials they have their conduction mechanism which is drift in the bulk of the grains and themionic emission or tunneling across grain boundaries.
In summary you can not speak for a saturation velocity for all materials.
Best wishes
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I am looking for physics-based measurements that can be performed in the edge plasma (upstream, not at the divertor) that yield the separatrix position or some boundary for it. Some of the methods I am working on:
- measure the profile of plasma potential, find the peak
- measure density or ion saturated current fluctuation, find zero skewness (inner boundary)
- measure the profile of electron temperature, electron density, heat flux etc., fit it with a "broken" double exponential and find the breaking point (outer boundary)
- measure the profile of poloidal velocity (cross-correlation of poloidally spaced probes, Er x B drift etc.) and find the zero
Some of the methods I have found (some thanks to the answers below):
- in H-mode, fit the pedestal Te or ne profile with the tanh function and find its center (can optionally be corrected for some fraction of the SOL width) [G. Porter, Physics of Plasmas 5, 1410 (1998)]
- (specific to field reversed configurations with a weak external plasma source) modulate the plasma source at a known frequency and measure the floating potential profile with a Langmuir probe; the region where the frequency amplitude goes down suddenly is the magnetic separatrix [answer by S. Cohen below]
- assuming pressure balance along the field line, map divertor pressure measurements to upstream (at the divertor, the strike point position is known, e.g. Eich function fit, maximum heat flux etc.) and match it to upstream pressure profile (this can also be done with the floating potential, electron temperature, heat flux...) [C. K. Tsui, Physics of Plasmas 24, 062508 (2017)]
- develop some really specialised probes [K. Uehara et al, 2006 Jpn. J. Appl. Phys. 45 L630]
- use the power balance criterion (AKA Stangeby's two-point model) to calculate the separatrix temperature, then find it on any measured Te profile [H J Sun et al 2017 Plasma Phys. Control. Fusion 59 105010]
I am open to any suggestions, links to previous research, or your personal experience (whether you've encountered the problem of not knowing exactly where the separatrix is, whether you think it's worth addressing etc.).
Guanghui Zhu Thank you for the suggestion. Could you please elaborate it? I'm not sure how I can infer the separatrix position from radiation distribution or temperature and density profiles. In both cases, I think that I'd have to make some additional assumption, such as "upstream separatrix temperature is 70 eV" supported by the two-point model.
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I am wondering is there any permanent torsion limit for buildings specified in the codes? for example how much a concrete building is allowed to twist permanently (due to foundation twist or structural plasticity) after very strong earthquakes or other extreme loads in different directions causing structural torsion? For permanent lateral drift, the limit is 1% for MCE shaking but cannot find anything for acceptable level of permanent twisting angle due to torsion.
Hello Dear Professor,
A file address attached below is a study about torsion in concrete building in Chalmers University.
Best Wishes
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Hello, after the analysis of volcanic deposits from South-East Asia by DRIFT Spectroscopy, some peaks occur around 1300-1250 cm-1 (please see the attached image). Do you know to which mineralogical compounds they could be associated? How can we interpreted it from a mineralogical point of view? Also this shifting between the spectra (around 1300-1250 cm-1) seems like a slight variations in the crystalline structures. Do you agree?
Have you examined the particles of the volcanic deposits using polarised light microscopy to get an idea about mineral type (or types) are present? I would imagine that the assemblage of minerals in the deposits from a known volcanic source are well-documented (e.g., acidic with lots of silica - granitic, or basic with less silica - basaltic). The presence of coloured (possibly pleochroic) minerals would indicate pyroxenes or amphiboles or if the minerals are colourless then that would suggest silicates such as quartz, feldspar, etc. When using analytical techniques, such as vibrational spectroscopy, don't forget that a quick look down a microscope at your sample can give you lots of valuable information about its composition and if it is a mixture, how many phases, etc.
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Among DRIFT and IRRAS spectroscopy,which one is more sensitive to detect in 1 % loading metal supported catalysis?
Dear Prof. Florencia Calaza
Thank you so much for the information.
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Because in my case, for 10 storied RC frame, drift values are coming maximum at the same node for every increase of intensity.
It may be at any point. It is required to be check.
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I would like to get suggestions for the optimal fiduciary marker for drift correction in PALM (Photoactivated localization microscopy) imaging with mEos2/mEos3.2 fluorescent protein? I was considering TetraSpeck beads, but the I am concerned about the high brightness of the TetraSpeck as this will saturate the detector when I use high laser power and camera gain for amplifying the signal of a single mEos2. Any other recommendations? Thanks
Gold nanoparticles around 100 nm diameter work ok; a little brighter than mEos2/3.2 with 561 nm excitation and typical RFP-ish emission filters. In my experience, something a bit brighter than that would be even better, but they work well enough if you have a few particles to average and/or have a moving average position over a few frames. Also because they aren't super bright they need to be in good focus. I would like to try >=200 nm diameter next time.
If you happen to be working with a fixed sample, an alternative is not using anything and using the data itself as drift correction; works if there is only slow xy drift.
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Sample is fungal and coated with Au/Pd and mounted with hot glue to the sample holder.
Image drift is worse at 5kV than 10kV
The image drift is visible on the high refresh rates used to navigate and only at higher magnifications (4500x +), but does not result in artifacts at photo quality refresh rates. If the sample was actually moving it should be represented as streaking in the low refresh rates, right?
That's odd. Usually the drift caused by charging is noticeable in all scanning speeds, although you see some distortion at lower speeds (photo quality) rather than movement. Furthermore, it is more evident in higher magnifications, since you are increasing the current density (smaller area and same current).
Did you try to use a conductive glue/paint or a carbon tape to fix your samples on the stub? I believe the hot glue is the cause of the drifting. You can also try to ground you sample with conductive paint/glue. If it is in a cover slip or other solid substrate, you can paint the edges. If it is a biological piece, you can try to paint the parts that are in contact with the hot glue and the hot glue itself. That could improve your grounding quality.
Good luck!
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I am viewing fixed phytoplankton cells (on cover plate) under SEM. I gold coated the sample with 30mAmp for 240 seconds and mounted the cover plate. First time when I observed the plate, the cells did not "move" at all. However, when I came back a few hours later to observe the same plate again, I could start seeing the cells on the image screen shifting at 5 um, and the shifting problem got worse when I came back to observe it the next day... The image usually moved in one direction. This prevents me from getting a high resolution picture since I cannot focus the image well. What factors can cause image shift? How can I address the issue?
Why do you need to keep your specimen in SEM for days?
What is the purpose of multiple observations of the same are?
If you see your specimen moving, it could be because:
Charging. Check if your specimen is well grounded. Sometimes after sputtering there are not enough gold on vertical edges of cover plates.
Soft mounting (like with carbon tape).
Stage instability, especially if you use specimen tilt. Avoid tilting.
SEM instability. Run SEM with a beam on for some time before you start taking pictures.
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The peak seismic drifts of steel MRFs are calculated by amplifying the elastic deformations due to the design lateral forces with a deflection amplification factor (DAF). The European and the Canadian codes define the DAF to be equal to the response modification factor R while the ASCE 7-10 defines the DAF to be equal to 0.6875R. Any thoughts about why there is this variance between the seismic codes.
R combines both the strength and deflection through the energy/toughness. Cd represents the deflection only. I personally attributes using smaller values for Cd than R to stability issues. Allowing Cd values close to R may be dangerous since the overall stability of the structure and surrounding elements of the seismic lateral system may be jeopardize and perhaps to control the second order internal forces.
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Did Miller detect ether-drift or something else? What could the something else be? Miller suggested that the Michaelson-Morley experiment did detect the same effect as Miller but at a much smaller than expected level.
(1) Dayton C. Miller, (1933) "The ether-drift experiment and the determination of the absolute motion of the Earth", Rev. Mod. Phys., vol. 5, July, p. 203. http://www.orgonelab.org/EtherDrift/MillerRMP1933.pdf
(2) James DeMeo, "Dayton Miller'sether-drift experiments: a fresh look", www.orgonelab.org/miller.htm
See my CNPS page at:
Printed book is most complete. Free book almost the same, but without math.
Abstracts: For instance "Einstein was right - who was wrong.
From _______________ John-Erik
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