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Dear scientific community,
i am currently trying to make more sense of the voluntary disclosure theory and the associated models. As far as i understood, the theory relies on the principal agent theory and incorporates the benefits for a company to reveal and provide more information then required by the lawmakers and other authorities. My questions are:
- Can the additional corporate reports and blog posts on sales, strategic partnerships or other aspects of the enterprise evolvement be assigned to this theory? Or is this theory strictly for accounting/ market popolicymaking?
- Is there any good literature review or paper describing the state of research on this theory?
- Is there any known paper transferring this theory into the setting of any kind of ecosystems such as platform ecosystems?
- Is there any research call to instantiate this theory for specific entrepreneurial phenomena?
I would be thankful for any advice.
Thank you a lot in advance.
Best Regards
Dimitri Petrik
Hello everyone,
I got a very confused result here. I treated cell with a drug which cause mTORC1 inhibition. In my western blot result, it shows, the redused mTORC1 group also showed a reduced the total protein level of P70S6K.(band density was quantified)
I wondered is it resonable to explain this results with the down-regulation of p-mTOR cause reduced p70S6K protein synthesis?
Thank you!
Among the plethora of biological modifications of proteins and nucleic acids, why is the phosphorylation process so universally abundant?
That is, compared to a variety of other possible molecular groups, is there a specific reason for biological systems to adopt phosphorus groups to the extent they do?
Is this just because of the abundance and metabolic economy of this group, or are there other considerations involved (e.g., bond energetics, physical properties, solubility etc.)
Or is this question itself misplaced? Please clarify!
Thank you :)
Dear fellow researchers,
while drafting an article about the importance and interlay of previous knowledge and learning with (multiple) external representations (combinations of text + pictures or diagrams etc.) Stumbled numerous times over cases of Expertise-Reversal-Effects, that seem not be explainable in the conventional terms of the Cognitive Load Theory (CLT) so far.
So, I would like to share these findings with you and to invite you to think about alternative explanations.
What is the Expertise-Reversal-Effect (ERE)?
The core idea behind the CLT is, that the better one's previous knowledge is organized (as chunks), the lesser one's working memory is loaded when solving problems or learning new contents. This holds true for most of the experimental observations. However, in some cases, high previous knowledge (HPK) leads to lesser performance outcomes than of participants with low previous knowledge (LPK). This effect is called the Expertise-Reversal-Effect (ERE): HPK learner profit less or even not from a specific treatment than their LKP counterparts.
How is the ERE explained in terms of the Cognitive Load Theory (CLT)?
For explaining this contradiction, CLT also proposes an executive moment of previous knowledge, that guides search & find processes. Those cognitive procedures could conflict with the instructional format as well as previous knowledge can conflict with the presented contents. So, as Slava Kalyuga states, "if external guidance is provided to learners who have sufficient knowledge base for dealing with the same units of information, learners would have to relate and reconcile the related components of available long-term memory base and externally provided guidance. Such integration processes may impose an additional working memory load and reduce resources available for learning new knowledge."
The fact that previous knowledge may induce additional cognitive load would explain lesser (absolute) learning outcomes of HPK learners with a specific treatment in comparison to their HPK counterparts without treatment. It would also explain lesser learning gains compared to their LPK counterparts with treatment (in case ceiling effects can be excluded).
However, it is difficult to follow this explanation for the case that HPK learners with treatment show lesser (absolute) learning outcomes than their LPK counterparts as this implies (by the interpretation of the CLT) that the instructional treatment must have had an enormous effect on cognitive load, overcompensating any advantages of previous knowledge.
Which evidences and limitations of the explanation given by the CLT have been observed?
There are convincing examples that undoubtedly trigger a cognitive conflict between the mental models of the participants and the presented information like in Schnotz & Bannert:
However, these experiments heavily (and intentionally) manipulated previous or presented knowledge to yield their effects. Most treatments we are much less pervasive and therefore their effects in terms of interference between previous knowledge and presented content (including treatment) should be milder. Furthermore, the ability to ignore treatments like signaling by color coding is not taken into account by CLT, it is however been demonstrated by eye tracking studies of Richter and Scheiter:
In this study, recall performance of HPK and LPK learners with that simple treatment equals, while for participants without treatment differ significantly as expected (cf. Fig. 3). The same for the comprehension measures in Richter, Wehrle & Scheiter (cf. Fig. 3):
Even more intriguing are findings by Kragten, Admiraal & Rijlarsdam, who report on an analysis of difficulties without any treatment of diagrams that low cognitive demanding diagrams (i.e. diagrams with low complexity) are even slightly better been understood by LPK than HPK learners. (Diagrams with high complexity instead show the expected characteristics.) Moreover, diagrams with unfamiliar conventions AND that poses high cognitive demands are being significantly better understood than those of eighter complex or with unfamiliar conventions (cf. Fig. 2):
These are some of the ERE findings that are particularly surprising and, in my humble opinion, cannot been explained in plausible way within the framework of CLT.
Is a Dual Processing hypothesis a sufficient candidate for explaining these findings?
Reading the book “Thinking fast and slow” by Daniel Kahnemann, I came across the hypothesis (to my knowledge originated by Stanovich and West) that there are two cognitive processes been postulated that govern problem solving and decision making in economics. According to that theory most cognitive processes in daily live (and learning) are done on an automated base relying on previously acquired cognitive schemata (system 1). These processes require minimal mental effort but are prone to errors. However, if system 1-processes do not lead to a sufficient solution or intentionally attention is shifted to the given problem, system 2 kicks in and starts deeper elaboration processes. So, perceiving hard to solve problems or being forced to shift focused attention to a given problem should significantly decrease error rate. Also see:
This theory has been recently applied to several fields, however to my knowledge not to learning and teaching so far and especially not to multimedia instructional design and external representations.
So my Questions for Discussion:
- In your opinion, is there a need for an alternative explanation of the Expertise-Reversal-Effect? (And why do you think so?)
- In your opinion, is the Dual Processing Theories a good candidate to explain the given data or are there even better ways to do so?
- In your opinion, how to predict an ERE before the experiment based on CLT or any other theory?
What do you think about the balance between exploring widely different designs vs. local optimization at different levels of biology (genomics, transcriptomics, proteomics, anatomy, etc.)? Which levels are more or less modular or plastic?
In the endocrine system, for example, one feels that having tropic hormones (i.e., those controlling the release of other signaling hormones at other glands) may offer a finer and perhaps more robust regulation, compared to a being where all hormones were non-tropic. However, the anatomic location of elements in these networks is not trivial. For example, in the renin-angiotensin-aldosterone system, renin is produced in the kidney, and aldosterone eventually exerts its effects in the kidney as well. However, the intermediate step by angiotensin-converting enzyme (ACE) mainly occurs in the lungs, which could introduce a delay in the regulation.
Do we have good explanations for the sites of production and action of different hormones in the body? Are there common principles to be learned as optimized by evolution in this respect? Or are happenstances/contingent evolution stronger determinants?
Thank you for sharing your thoughts!
We used to associate G proteins to most beneficial receptor functions & β-arrestin proteins to GPCRs internalization/signaling termination … But, do you think β-arrestins could contribute to GPCRs’ desired effects? Alternatively, could G proteins contribute to the development GPCRs’ side effects?
i want a software to detect the n-terminal, hydrophobic, and c-terminal regions of signal peptides.
any one knows???
thank you
How does the awareness that plants are intelligent can help plant scientists? May it be a new school of thought in realm of plant studies?
I don't understand why in much article and book about VLC IM-DD it's written that one can use an OFDM + QAM modulation.
The trick should be the hermitian simmetry imposed on the transmitter but, if i impose that the signal becomes real.
If the signal is real how can i transmit a QAM? How can i receive the phase?
Take a look at the notch signaling pathway in human from KEGG : https://www.genome.jp/kegg-bin/show_pathway?hsa04330
What is Fringe activating? It is not pointing to another gene or protein, it is pointing to an interaction. What does that mean?
Hi I am confused about the concept of signal quality index. what is signal quality index? what is the relation between signal quality index and signal strength? can we determine signal strength from signal quality index?
I want to find the magnitude and phase of electric power signal i-e x(t)=220.cos(2.pi.60+pi/5) Using DFT in MATLAB using sampling frequency 1kHz.
but I am confused about how to acquire one cycle of the sampled signal then apply DFT on that.
Ultrasonic backscattering signals analysis in solid media
Hello Mario, I am not sure if you are still interested in this problem. I have gone through the codes and to be honest, I could not find any issue. However, using 'calc_scat' function in place of 'calc_scat_all' helped me to get around the problem. Please see attached the resulting figures. According to my understanding, both functions should give same results for piston transducer. I am not sure why we are getting different results. I will be happy to hear about your opinion on this.
Steroid hormones are usually transported in the blood stream by carrier proteins. At their target cells they are released and can then either bind to surface receptors or diffuse through the plasma membrane due to their lipophilic nature. In the cell they are bound to receptors that enter the nucleus and influence gene expression. Some aspects of this model are not clear to me:
1.) How do carrier proteins in the bloodstream "know" when to release the hormones? How are target cells recognized? The ability of steroid hormones to directly pass the plasma membrane makes specificity somewhat difficult to achieve.
2.) So most steroids can pass through the plasma membrane because they are lipophilic. But then they have to travel through the hydrophilic cytoplasm to reach their destination. Are steroid hormones amphiphilic? Or are they immediately bound to a receptor protein once they pass the plasma membrane?
3.) If steroid hormones are capable to pass the plasma membrane they should also be able to pass the nuclear membrane without being bound to a receptor protein, yet this does not seem to be the case. The lipid composition of plasma and nuclear membrane is different, but can this explain the differential diffusion behaviour of steroid hormones?
4.) How are steroid hormones that have served their purpose removed from the cell? Are there deactivating enzymes? If yes, how are these regulated? Or can the steroid hormones, once released from their receptors, simply diffuse out of the cell? If this is the case, how is a "re-binding" of the hormone to another receptor protein prevented?
I would appreciate if somebody could help me with these questions and/or point me to literature that explains these processes in more detail.
What is the best way to convert RF signals into energy .
How we can store this energy for future use ?
I have a plant with transfer function, I design a PID Controller and the output response of the plant along with controller can be obtained with Ziegler method. What is meant by control signal, how to get response for it?
What would be the confidence level of points selection for the quantification of area under a signal ?
Azadeh Mansouri Mansourabad
while the data acquisition process is made with EEG signal, ordinary differential equations is enough to model that?
I have generated a DMT signal on AWG (tektronix 70002A) and then used it to modulate LED(the signal is DC-biased to have voltages above LED threshold).
The signal after photo detection is captured on oscilloscope along with the back to back signal from AWG (A direct coax connection between AWG and oscilloscope).
For back-to back connection, the Sampled data from oscilloscope (25000 sample points) is compared with the input DMT signal shape. It is observed that the input DMT signal can be reconstructed by using the samples between 15227 to 16384. Fig1. Thus the start and end points are identified within the above range.
But the signal after photo-detection (Fig2.) is totally unidentifiable for the corresponding start and end points. Will the aforementioned sample points are the start and end points for the detected signal? Does the delay due to optical and coaxial lengths create significant shift in the start and end points between the signals? Any better method to identify the start and end of the DMT signal?
For example the molecular ion of R4NCl and R4NBr or R4NOAc would have same or different retention time in LCMS or HPLC?
Generally, PID controller holds set of input set point which helps to reduce error rate (e). Further it gains the output signal (u). But Still there is a confusion, that how it is used in DC Motors.
its looking like i have very low Q range signal and particle have so much polydispersity .so the intenty showing me no damping .Is that normal in SAXS intensty?
I am modulating an OOK signal(square wave) of 100 MHz. The electrical signal after photodetection shows a frequency of 20 MHz. The amplifiers used in my system are capable of handling 100 MHz.
Can someone help me understand this difference ? Is this due to LED non-linearity or does the ratio 1:5 has some significance?
Hi, I started the experiment from low frequency square wave (5 MHz) and obtained the following result(green-direct signal from AWG) and (pink-Signal after photodetection). It shows that there is some phase shift(delay) and also distortion. But I do not understand why the peaks are not uniform in their amplitude?
and if i modify the above ckt so that cap will discharge during off period of clock and it will charge during on period?
I am measuring a photoresponse of graphene devices using lock in preamplifier SR830. I would like to analyse the photoresponse dependence on back gate bias. As an easy solution, I've used computer controlled Keithley 2636B. However, whenever the bias is changed on Keithley it makes massive spikes in the signal detected by lock in. I've tried varying the chopping frequency, no result. I am quite confused, since I am not sure why this is happening. I've contacted Keithley, but unfortunately they were not helpful. I've contacted Stanford research but never got their reply. The set up configuration is as following: source/drain of the photodetector are connected as A and B for the lock in to provide A-B measurement, the drain and back gate are connected to the Keithley. It should be noted that drain has both lock in preamp and Keithley connected, this contact is also put on the ground.
How to calculate PESQ (Perceptual Evaluation of Speech Quality) Score of any noisy speech signal, especially, whose speech signals which have sampling frequency 12 kHz.
I want to train a machine learning model which can evaluate one's visual fatigue level caused by 3DTV though EEG signals. The problem is subjects can not evaluate themselves properly.
my research includes finding the optimal values for the gains of PI controller...my model results on different max. overshoot of error signal for different gain values...however, the steady state error and the settling time seem to be unchanged for the gain ranges settings...can anyone help me find other parameter or constraint to judge the error signal other than the max. overshoot, the settling time, or the steady state error?
Is it possible that there is a kind of amplifying mechanism, that just like EDFA to amplify 1550 nm optical light, to amplify ultrasound signal?
In most of the voltage control loop applications, the input variables to a PI controller are reference voltage and actual voltage and the output is usually a current signal. How the controller converts the difference of two voltage signals to current signal?
Is it possible to send electrical signale through a single conductor without electrical ground ?
- would the signal be noisy with desalted oligos? Tm around 60C.
We tend to use P32 as a radioactive label for the probe.
Are there any region that can give no signal with this technique? Any literature about it?
Hi everybody,
I've made a stable line for a Flag-tagged protein.
While the signal of the protein is very strong by immunoblotting, I've no signal when I blot for Flag. The positive control (a transient overexpression of another vector flag-tagged) is fine, so my antibody works.
I'm wondering if it is a matter of recognizing the epitope and, if yes, what I can do to let the antibody to bind the flag.
Thanks to anyone can help me!
Is there any database, from where I can collect stress ECG signal (Like MIT-BIH database)?
I am trying to analyze a 27 Al MQ MAS NMR spectrum of alumina but I have doubts about signals. I want to talk about the experiment and the information that I can obtain about it.
If I can also establish LOQ using a calibration curve, is it OK if my lowest level is <10 signal to noise? Or will this introduce error into my method?
I would like to know which software is the most commonly used or recommended for this analysis.
Best regards,
Cristian
I know this depends in part on the sensitivity of the antibody, but is there a general range of ug or ng that is considered appropriate for getting a good signal?
I don't have a manifold so I will be manually dropping 1-5uL, protein concentration is roughly 2mg/mL.
Developed an amplifier circuit to power up the speaker with a signal generated from function generator in the audio frequency range with manually changing amplitude and freq. of the signal. Now I have to find the speaker cone displacement using any method. I am currently looking at current sense circuit(Low side). But not able to understand the result! Can anyone tell me the feasible method to measure the exact displacement of speaker cone?
I also want some relationship with applied signal amplitude with displacement of speaker cone?
Please help.
Some special type of proteins (opsins) play major role in sensing color in eyes. what is the molecular structure of theses proteins and what is the mechanism of sensing of intensities and colors/wavelengths. How the opsins convert photo signal into electrical signal?
For a single wireless link monte carlo simulation the decision variable is
Conugate( h.y) where h is channel coefficient any is received signal.
What is the decision variable for full dulpex relay simulation
what are advantages/disadvantages of adding gaussia luciferase on N terminus than on C terminus of the protein of interest.
and would it work if I attach the gluc signal peptide at the N- terminus of the protein of interest and leave the gluciferase on the C- terminus of the protein of interest?
Hi, in GSM localization application, can anyone tell me the relationship between the signal noise measurement and the variation in signal distance.
My research field is Localization Based Services in GSM system using fingerprinting method. Which is based on the signal distance computation.
I want to calculate the antisymmetry of an ultrasonic crack signal. Please guide me that how can I do that?
I am studying how different filter parameters affect the perception of timbre in synthetic vowels. I have been using a sawtooth signal, which is good a signal, but sounds a bit harsh and not quite 'organic' to my liking.
Can you suggest a better synthetic (reverse-filtered ?) alternative to the sawtooth wave for filter shaping?
I wonder if we can agree upon a certain voice source - and take it as a standard for synthetic vowel stimuli? That would be a step towards further parametrization of stimuli used in psychoacoustic study of vowels and timbre perception.
How to decide or select a signal peptide for the overproduction of monoclonal antibody? what are the factors to be taken care of when selecting the signal peptide? answers with example will be of great help.
Thank you.
hi
signal peptides are commonly protein-specific, I wonder if there is "general" signal peptides which can be used among plants. Hereby, it would enable more convenient protein expressions in various plants.
Your responses would be really appreciated.
Thank you.
Hi all,
I wanted to do the small signal analysis of NE 39 bus system for my research. Is there any software for doing the same? Could anyone guide me on how to do the same?
Thanks in advance
In some trial I found that using Katz fractal dimension I get 4 or 6 for two dimensional data? Is it correct if I use it as feature of the signal?..
I repeatedly get very low plasmid after isolation recently. I tried using 3 different kits but the problem persists. I usually put my cultures for growing over night and isolate the plasmid the next morning. Any body has faced this problem before? this is specifically getting serious because every time i send my samples for sequencing they return them back cuz there was no signal or very weak signal due to the low quality/OD of my plasmid.
I am working on a map of metal sorption in microbial samples. The basic method is to use a specific fluorescent probe to label the target metal ions, which could be excited with the proper laser, followed by the collection of the fluorescent signal to map the native spatial distribution of these metals. Hopefully this could transform the fluorescent intensity to target metal concentration. But to calibrate the signal intensity to different metal concentration is always difficult since there was no clear evidence that they process linear relationship between these. So, has anybody ever done such calibration before or have any ideas to prevent fluorescent deviation during your test?
Hello!
I did some in vitro digestions according to the INFOGEST (Minekus) protocol. When I analysed by immunobloting the different aliquots of the digestion I observed "background" signals that correspond to the size of the various digestive enzymes: pepsin but specially intense are the signals from trypsin and chymotrypsin (these last ones of a similar size of my protein of interest).
I found some publications where is described that enzymes such trypsin and chymotrypsin can actually break up the substrate and produce chemiluminiscence...
Does someone know a way to avoid this?
Thank you in advance!
I am modulating an optical signal with carrier frequency (1 GHz to 20 GHz). At lower carrier frequency (1 GHz), the side-bands are separated by low distance. But the distance becomes higher when the carrier frequency increased (20 GHz). How can I explain this phenomena with Fourier transform?
Which portion of the Ultrasonic Time Signal (Ref.attached file) could be considered for analyzing it for microstructural damages?
Hello, what I want to ask: How do you decide which area of the tumour ist the best for counting? How do you go on with, if there in one slide are areas without any signals, for example good signals in the periphere and no signals in the center ? How do you interpretate, if there are only green ( control ) signals , is it loss of 1p or 19q, or will we have to do it again ?
A signal is transmitted by the transmitter and multiple rays arrive at the receiver as a result of reflections (from the flat obstacles), diffraction (from the edges of obstacles) and scattering.
How do I find the number of clusters in this condition?
I have generated my dataset.Now i want to train them with ANN tool of
MATLAB.
I started working on DSP TMS320F28335, in pin configuration I have a set of five pins of ADC given as input of +5V to -5V, and other sset of pins ADC given as 0 to 3V. but how to proceed to give sinusoidal input to the DSP. Is it really possible to give AC signals to ADC converter
The transient nature of the radio meteor event makes FFTs unsuitable for analysis and I am looking for alternative techniques.
Hi, actually I'd like to apply the machine learning technique to extract the human intention from the EMG signals. Maybe some of you have already collected such kind of data, and I'd be very grateful if you could share it with me. Thank you in advance.
Hi,
I'm currently trying to run cudaica after using pca to reduce the number of dimensions using the following process:
- remove mean
- define number of components explaining 90% of the variance
- whiten
- ica using whitened signal
My problem now comes with trying to compute the projections from the output, and then how to reconstruct the data with the original numbers of channels.
I am working on a research work on transmitting ECG signals compressed by Compressed sensing over wireless body area network . The signal is affected by noise and small scale fading. The normalized mean square error is used to estimate the quality of the reconstructed signal at the receiver. When I run the same m file in matlab several times, I obtain different values for the mean square error, although the same channel signal to noise ratio is used. I think this is reasonable, do you agree? If so, how can I obtain a signal value to represent the quality of the reconstructed signal at the receiver?
What might cause a recombinant protein not to be secreted to the extracellular matrix otherwise getting stucked in the cell. This is a domain of a recombinatly expressed extracellular protein and everything seems to be fine with the signal peptide sequence and cells looks healthy
hi dear all.assume that a chaotic signal is received from the two different noisy channels. can we measure the effect of noise on a chaotic signal using the Lyapunov exponent? or you prefer another statistical or feature extraction method? thanks
i have problem to measure the parameter of the signal (Frequency,Amplitude, Initial phase shift) which lower than 1Hz (ex. 0.1Hz ,0.01Hz).
I have a task to Implement boundry scan and Verify IO Pads of My design using P1500 Bcell, But as we dont have dedicated state machine for P1500 protocol as we have for 1149.1 protocol. so I want to use 1149.1 state machine and p1500 Bcell at IO pad level so is it possible??
I am not getting exact signal mapping from 1149.1 to 1500 protocol.
If anyone knows about this then let me know please....
Dear Researchers,
Anyone can help in defining the 1-bit compressive sensing, I have some difficulties to understand how it works exactly. Is the algorithm can be applied to analog/digital signals?
Thanks,
I am Infiltering my BiFC constructs along with a localization marker. The localization marker has RFP. I can very clearly see RFP signal, but I am not able to find GFP signal so far. I have already repeated my experiments three time. Any suggestions?
Hello every one, I am trying to obtain the spectrum of non-uniform sampled signal.
Suppose the signal is sampled approximately every 10 micro seconds, and satisfies the Nyquist-Shannon sampling condition. The sampling points are:
(0±sigma)ms, (11±sigma)ms, (21±sigma)ms, (29±sigma) ms.
Where 0, 11, 21, 29 are the center of the non-uniform sampling (which are known), and sigma is the jitter level.
How can I get the spectrum of a signal with this kind of characteristic? Can I polyfit the signal and resample it? How the sigma affect the spectrum?
Welcome to discussion and thank you very much for your help.
I want to create a global system to comunicate arduino and android app with a database and webpage.
First i got the raw signal from a biomedical device and store in a microsd in the arduino, next i want to send this signal via bluetooth to a android app, next save this signal in a database.
Finally i want to create a webpage that can comunicate with this Database as the android app.
I have made predictive current control for dc to ac two level 3 phase. When doing THD analysis i get 8.39% whereas 5% is acceptable. How can i get the desired THD levels
Hi, I am looking into some signaling lipids from marine copepods and just found out that they are present in fresh water copepods too. Now I am trying to get samples of from different species. So my question is if someone has freshwater copepods of a known species in the lab and can spare me a few?
Best wishes /Erik
I am working in EEG signal by matlab I use(EEGLAB) I have a data about(5*2886000), but I have those 3 questions:
1.Is it better if we have more channel in EEG signal?
2. We have 5 row(5*2,800,000) can we change row to bigger than 5 , provided that the data does not change?
3. Why we use 5 five steps(5 times) for sub band to separate(High path and Low path)? what happen if we use more or less than 5 times ?
does it has any relation with Gamma, Beta, Alpha, Theata?
thanks...
I have sEMG data I want to apply EMD to extract features in time frequency domain. I decide to take mean frequency and power spectrum density of my IMF. how can I get frequency range of my each IMF?
which protein gets phosphorylated by PKczeta in nFkB signaling?
I am using PVDF/nitrocellulose membrane for blotting. I have tried different ELCs( ECL Pierce, ECL Prime and Super Signal Femto) to have better signal, and tried different exposition times. Also, I have rinsed my membrane with TTBS (tbs 10x +900ml dH2o +1ML tween20) more and less times than normal protocol. If I rinse more, frequently I have lost signal. If I rinse less than normal protocol, more dirty background appears. May I ask your recommendations on this problem how I can solve this problem? Thanks in advance.
How to measure the noise of the transimpedance circuit by using the oscilloscope？shorting the interveting input terminal or opening it? And the bandwidth was measured by applying a sinusoidal signal with a resistor of several MΩ to the input，and then observe the attenuation of output voltage from the oscllloscope with the change of the sinusoidal signal frequency.This measurement way is right or wrong?
Hi,
In Statistical signal processing, lot of research is based on complex analysis. Many techniques and methods are transformed to complex domain. Whereas complex information is only important in form of magnitude and phase. So whats the difference in using magnitude information or real and imaginary information of the data? Why is phase important? What the difference of the signal that is added with phase information and without phase information?
Appreciate your comments
we do not have the fundamental frequency
Hello,
We are trying to monitor in vivo proliferation of CD4+T cells by using CFSE labelled cells. This is what we tried so far without any success.
We purified total CD4+T cells or naive CD4+T cells from CD45.1+ mice spleen using Miltenyi kit. Then we label the cells with CFSE . We took a small aliquote of CFSE labelled cells and surface stained them with CD3 and CD4 antibodies. From that we know that the cells are very pure ( more than 95% live, 97-98% CD3+CD4+) and we saw a very bright and narrow peak of CFSE. Right after CFSE labeling, we counted the cell number and injected either 4 million or 10 million of labelled cells in SCID mice (also cd45.1 back ground) by IV injection. Then we took down the the SCID mice either day 2 or day 5 after injection. When we checked the spleen and blood cells of the SCID mice for CFSE signal, we didnt see any signal above background, also we noticed less than one percent of CD3 and CD4+ cells. We are trying to solve this problem. Any suggestions will be highly appreciated.
Thanks.
I am working in glow discharge plasma system. Frequency of my experimental signals are 400-600Hz..I have found FIFO memorise is used for delaying a system. Can anyone suggest the electronic specifications? Is there any other method can be used for the purpose?
I am using FFT algorithm for a transient signal.
If I dont use average for FFT, my frequency signal is not true?Is it necessary to use average in FFT?
I want to extract modal parameters fro
I am using circlefit method but my modal constants(phi(1)*phi(2)) are not mass normalized and I have only FRF graph. how can I do it?
We are trying to classify different waveform (1-D signal). So far we are trying Pearson correlation with the training samples, and it is working reasonably well. However, we are facing few issues:
1. The testing waveform is concatenated (in a continuous manner) and different waveform have different length. So, selecting a window length for correlation is a problem.
2. Because of the variable length of different waveform, if we classify one waveform wrong, the alignment of the rest of the waveform is messed up. So, the classification of the rest of the wave does not work well.
Is there any better way to classify waveform/signal other than correlation? What would the machine learning approach for this problem? What are the common features for classifying 1D signals?
Thank you so much.
regards,
Haider
Already my senior scholar developed SODAR software using vc++, but i want design a software using C#
Is there any possibilities to design a software to find wind direction(vertical,horizontal), facsimile record,received signal in time domain,frequency domain in SODAR signal using C# or Java
We measured signal X in two methods(M1, M2), and we want to compare the two signals Xm1, Xm2. What's the best method to measure the similarity between the two signals and the information content, in other words, how can we approve that the measuring methods didn't affect the content of signals ? do we need to measuring similarities or studying information content?.
I am working on analog schematics using Cadence Virtuoso. While simulating the testbench, I specify certain rise and fall time for particular frequency. Is there any range of rise/fall time related to the frequency of the input signal I should use?
Thanks in advance.
Hi guys,
I recently used anti c-myc antibody purchased from Sigma (C3956) to do whole mount immunostaining. However, the signal appered somtimes. In most cases, no signal. Does anybody know this? Which antibody do you use? Any suggestion is welcome.
Thanks a lot!
We have problems with in situ hybridization(no signal) when using DIG-labeled riboprobes but not when using biotin-labeled. Dig probes worked just fine for many years until this year. Does anyone have the same problem?
In the paper linked they normalize their signal using the equation sumt(Re(Rc(t)))Rc(t) = 1. However this is the first time that I've seen such a normalization. Does anyone know to use this normalization equation? Because when it comes to normalization I thought it was meant to divide the signal or vector by its norm but this method is new to me. Any help is appreciated.
For instance if i have two physiological signal (ECG,BCG) for example, how can i accurately measure similarities between them? Is mutual information an option? Please help me out.
I would be grateful if someone could recommend me some good introductory resources to the application of graph theory analysis to EEG signals.
Thank you in advance
I am a research scholar of I.S.M dhanbad, my research area is sensor development. I got non linear out put signal like quadratic so i want to change in linear so any one have idea please give me.
hello researcher, i just want to ask if the discrete wavelet transform can extract each individual harmonic frequency alone of a distorted signal or it only extracts the fundamental??
There are many ways to normalize data. When it comes to neuronal activity indicated by GCaMP, which way is better considering the biological meaning?
Dear all,
I am wondering if there is anyway to develop a positive control for ROS generation study in plants. In principle, I have higher signal in stressed plants compared to non-stressed but our concern is to validate if the signal really associated with ROS. So, I am just wondering how can I generate ROS in healthy plants and then compare the strength of signal with both stressed and non-stressed plant parts. Do you have any suggestion(s)?
Thanks in advance.
Muhammad
