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# Detection - Science topic

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How to generate standard curve for antibiotic sample in spectrophotometer?
Prepare solutions of the antibiotic at various concentrations in the desired solvent. Use a spectrophotometer to measure the absorbance spectrum of the solutions over the desired range of wavelengths. Make sure to use a clean cuvette, which should be quartz if you plan to make measurements in the UV range. Make sure the samples fill the cuvette.
Discard the concentrations that go off-scale for the instrument. A maximum absorbance of about 1 is desirable. Subtract any background from the solvent.
Choose the wavelength of interest. This is usually the wavelength with the highest absorbance, but you may choose a longer wavelength if the maximal absorbance occurs very far down in the UV.
Plot a graph of absorbance versus antibiotic concentration at the chosen wavelength. Perform a linear regression through the data points. This is your standard curve. The slope of the standard curve is the extinction coefficient for the precise conditions used to make the measurements.
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Can anyone provide me with deep-learning python code to detect the QR codes in natural scene image then scan and read them?
I am not sure but you will find your solution here https://herbnews.net/how-do-i-make-my-herb-garden-attractive/
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In a signal is to be transmismitted, first pilot symbols are added and then through Mach-zehnder modulator it has to be transmitted for optical communication purposes. So, for pilot symbols, they have to be go through Mach-Zehnder modulator. The output of Mach-Zehnder modulator is E_out=cos(phi); Where phi= ((U+U_dc)/U_pi)*pi. and here, U_dc, U_pi and pi are constant. And U is the information after inserting pilots. This signal E_out is sent through the channel h.
Now, my question is that how should I estimate the channel because the pilot are gone through Mach-Zehnder modulator before the channel. and How should I extract the pilots and estimate the channel? Thank you.
If we see the series expansion of cos function then how can we find the linear interval? After first term every term is non-linear. I am attaching the series expansion of cos function. If I am missing something in this concept please let me know.
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Hi all,
I am working on an ECG QRS detection algorithm which I did implement it using C language.  The code detects the ECG peaks regardless of the beat type (Normal, Paced, … etc.) and it saves the detected peaks into a text file as time location of the peak.
To evaluate my algorithm I have to compare the obtained peaks to those provided in the reference annotation files (MIT-BIH arrhythmia database). By comparison I can find the FP and FN peaks, and then calculate the sensitivity and positive predictivity from them. The main objective to find all of the peaks and not the type of the beat.
According to the Physionet guide, using the “WFDB Software Package" in "Cygwin” I have to do the following:
1. Use “rdann” and “wrann” functions to convert my text file into a compatible annotation file.
2. Use “bxb” function to compare my obtained beat annotations beat-by-beat to the reference annotations. (Ex.: bxb -r 100 -a atr yow -L bxb.out sd.out)
I am looking for few clear examples showing how to convert the text file into an annotation file and then compare the annotations to the referenced ones. I also tried “rr2ann” function to convert my text file into an annotation file but it did not work for me.
Thanks :)
Have you considered the wfdb-python library (https://github.com/MIT-LCP/wfdb-python)? It has QRS evaluation support. It is a pure Python library. Hence it runs on all platforms without any need for compilation. In particular, in the wfdb.processing library, there is a function wfdb.processing.compare_annotations, which can be used to compare the reference annotations against a test annotation generated by your detector.
The demo notebook provided by them describes how to use it: https://nbviewer.org/github/MIT-LCP/wfdb-python/blob/main/demo.ipynb
In particular, you provide
- reference annotations [the list of indices at which R peaks have been marked]
- test annotations [the list of indices at which your QRS detector has detected R peaks]
- the window width where you allow a matching annotation to be found. Thus there may be a difference of a few samples/indices in the reference and your algorithm's annotations
- the ECG signal on which the annotations were done.
The function then identifies the true positives, false positives, and false negatives. It reports the sensitivity and positive predictivity of your detector. You can also access the list of indices for false positives and false negatives for further analysis.
Following is the rough sample code:
comparitor = wfdb.processing.compare_annotations(ref_sample=ref_sample,
test_sample=test_sample,
window_width=window_width,
signal=signal)
# print the results
comparitor.print_summary()
if comparitor.fp > 0:
print(f'False positives: {comparitor.unmatched_test_sample}')
if comparitor.fn > 0:
print(f'False negatives: {comparitor.unmatched_ref_sample}')
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Is there any effect of damage shape on the damage severity? And which do you expect has more severity of damage the holes shape or longitudinal shape? And why?
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I am looking to measure small amounts of heparin released from a material that had heparin incorporated during fabrication. I would like to accurately verify and quantify the release of the heparin over time from 1-21 days post fabrication. I am aware of a \$600 detection kit. Is there a cheaper method/kit?
Hi,
Please check out following article.
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Does anyone get errors with using the Recognition part in " Scene Text Detection and Recognition by CRAFT and a Four-Stage Network" ?
etecting and Recognizing texts for a given natural scene image using EAST and Tesseract Algorithms.
Regards,
Shafagat
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Dear Experts, In order to apply carbon dots (CDs) for the removal of analytes, why do we need to encapsulate these nanodots with other materials? Is it possible to use CDs as a lone adsorbent? Thanks in advance for your valuable comments.
Considering the fluorescence origin, CDs were encapsulated in silica matrices by reacting a silane precursor with surface hydroxy groups that do not contribute to the emission process. It enables CDs in the uniform dispersion in silica to preserve their narrow emission in the solid state by avoiding aggregation.
To enhance the optical properties, stability and to preserve emissions
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Do we have to classify lethal weapons based on size , shape or temperature?
This is possible. I am working on it
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Hi everyone! I am looking for a dataset and I'm gonna be so thankful if anyone helps me by introducing any link to access databases. I want to research on knock detection in spark ignition engines by processing of vibratory signals. so first, I wanna validate a pervious study in this field. Thus, I am looking for a dataset and related researches that were done before according to the databases.
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I’m a graduate student and I’m going To start my thesis research , could you help me to find something related to the islanding detection to research about ,thank you at all
i am interested too and follow
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We are working on mammogram images. And want to detection the bounded of the tumor via the segmentation method. Specifically, we like to use ACTIVE contour and level set technique. But do not clearly understand the difference between them.
There are two main approaches in active contours based on the mathematic implementation: snakes and level sets. Snakes explicitly move predeﬁned snake points based on an energy minimization scheme, while level set approaches movecontours implicitly as a particular level of a function.
Regards,
Shafagat
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I have tried tabula-py library and java tool so far but it results in many false positives ( i.e. telling that a table is present when not the case).
Some of the cases were
content 1 content 3
content 2 content 4
If text is written in the above manner, then also it marks it as tabular data. Is there any solution that does the task better and handles the above problem. ( including Deep learning or other techniques).
The Excalibur, which is built on top of camelot:
Best Software to Extract Tables from PDF (and export them to Excel, CSV, …)
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I've been trying to detect mScarlet protein purified from E. coli via an ELISA assay. My protein has two tags: an N-terminal Strep-tag and a C-terminal His-tag. To do the ELISA I've used Streptavidin Coated Plates (https://www.thermofisher.com/order/catalog/product/15500#/15500) so that the Strep-tag attaches to the plate and then using an anti-His antibody for the detection of the protein. However, not only we've observed low signal on our samples which are similar to our negative control.
On another pilot test I used 96 well high binding cell culture plates and no BSA blocking, and this time around the negative control shows more signal than the purified mScarlet samples.
If anyones knows what could be going wrong, your help would be very much appreciated.
First check your protein reactivity in western blotting (both strep tag and his tag)
Confirm your protein is in soluble fraction. Usually proteins starts precipitating after dialysis and aggregates if your buffer composition is not suitable to protein.
If you explain little bit about your purification dialysis its helps us for better analysis.
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How to get access to LYON19 dataset? histopathological image dataset of Lymphocytes provided by LYON19 challenge is not accessible from its challenge site https://lyon19.grand-challenge.org/Background/ .
Train dataset not available in this chalange..
" No training set is provided, participants should use their own data to develop a method. "
Test data can be downloaded from the  Zenodo platform
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I am preparing reduced graphene oxide by using plant extracts...I was thinking if I could use TLC (in addition to UV and IR) to detect the reduction reaction by the increase of hydrophobicity which might result in an increased RF when using an organic solvent.
thank you all very much
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FTIR technology is considered the most advance for the detection of adulterants in milk. Is there any mathematical relation that can describe the relationship between the amount of adulterants in milk using the absorbance from the FTIR? Please suggest any research articles that describe this or related areas.
Relation between milk with adulterants . Many times urea is added in the milk as adulterant to increase the density. If you is isolated then in FTIR it shows the absorption for NH2(V NH = 3200-3350 cm-1) and C=O) at (v 1700 cmi1).
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We are performing electrocatalytic CO2 reduction experiments and are unable to measure the low quantities of CO that we are producing. This may be due to a large excess of CO2 (20 mL/min) that we are flowing through the cell.
We are using Soprane GC machine with Molecular sieve 5A, 10 m long column.
Dipak Shinde Molecular Sieves %A column is only useful for elution of O2,N2,CH4 and CO when connected to TCD detector .Note That CO2 could not be detected using the same column. The detection limit of your detector needs to be validated first possibly by passing lowest concentration of products that you may form i.e CO gas.Secondly if your detector is sensitive enough to detect the concentration then injector volume,split ratio of injector can be changed to obtain desired peak for CO. Lastly the CO2 electro-reduction i.e. CO2 conversion could be very less which gives lower concentrations of CO which can be improved by process optimization. Find attached document which can help you to develop method for elution of CO and other permanent gases.
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I'm trying to implement a fall detection algortihm written in C in a Zybo board.
I am using Vivado HLS.
I don't know how to start even if already did the tutorials related to Zynq7000.
Thank you for any help.
V. Carletti, A. Greco, A. Saggese, and M. Vento, "A smartphone-based system for detecting falls using anomaly detection," in ICIAP 2017 Proceedings, 2017. [Online] Available: https://link.springer.com/chapter/10.1007/978-3-319-68548-9_45
V. Carletti, A. Greco, V. Vigilante, and M. Vento, "A wearable embedded system for detecting accidents while running," in VISAPP 2018 - Proceedings of the International Conference on Computer Vision Theory and Applications, 2018. [Online] Available: https://www.scitepress.org/Papers/2018/66128/66128.pdf
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Where can I get the signal-to-noise ratio values for detection limit, significant detection, etc for XMM-Newton's EPIC pn data ? Can someone suggest any reference ?
Signal -noise ratio can be obtained from the Gaussian noise distribution
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Hello,
I am new with occupancy models, and I am working on selecting a model-fitting function for an occupancy model to use for a camera trap study that incorporates abundance and multiple seasons into detection. I hope to use unmarked in R, though I am open to other options. The Royle and Nichols 2003 function (occuRN) seems to be best for using abundance models, while the MacKenzie et al. 2003 (colext) function seems to be used for multi-seasons. My study design is as follows:
• 3 summers of data collection, camera traps deployed in backyards
• Cameras deployed 2X per season in each backyard for 7 days at a time
• 2 cameras in each yard per deployment (at the same time)
I realize that I will have to account for the spatial and temporal autocorrelation, and that they can't be treated as independent samples, but having 2 cameras per deployment may give me a unique advantage to modeling detection. They were always deployed in roughly the same areas of the yard with roughly the same amount of cover and other habitat metrics. Should I be utilizing the multiple season functions, the abundance-informed functions, or another type of function?
Thank you for your assistance!
I am also looking same question description for my camera trapping data.multiple species and multiple season.
each camera duration of each species divide in a week.each week let's five presence of bears.you need consided 1.its means for first week your dectection is one..then check red fox week one..let's suppose five detention.but you need consided 1.then second week for each species and each season..RPRENCE or presence you can uses.Gamm. model you can used
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I have run a power analysis on my occupancy models that says for a power of 0.85, and using 204 sample units with 11 replicates, the detection probability would need to be about 0.096.
How can I convert this detection probability to tell me how many detections (1's) would need to be in my detection history for that to be the detection probability?
Thanks for any help!
I think it's circular reasoning because the detection probability is calculated using your criteria, which already include the detections!
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How long could injected BrdU exist in the body and be detected by BrdU assay once it is incorporated into the proliferating cells?  Last until the cell death? Thanks very much!
Hi,
do you know the answer yet? how long could BrdU incorporated into DNA stay?
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I would like to detect any moving object (in particular human) from a distance of 10-15 meter. Is it possible to implement such sort of system using Arduino and PixyCam?
Any information regarding this issue would be highly appreciated.
You can, however for less distance. And PixyCam is good for tracking colors. So if the moving object has any specific color, then things would become easy for you
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Hi All,
I have a protein of interest, X, and it has a single phosphorylation site identified. Another protein A might dephosphorylate X. I want to knock down A, and quantify the change of phosphorylation on X. The problem is I don't have antibody against the phosphorylated X. Is there any other way that I can detect the phosphorylation level on the protein? Thank you!
Going to be challenging...how much material do you have? You could try pSer/pThr or pY combined with a protein specific IP...probably your best option.
Quite simple if your protein genuinely has a single phosphorylation, much harder to link to your phosphatase if there are more phospho sites (quite possible); if there are more, the contribution of your site to the whole protein phosphorylation might be lost in the noise. Ditto for the Phos-tag approach suggested above.
If you have enough material, mass spec might be your best option, although whether it will be quantitative enough to test phosphatase X contribution has to be empirically tested.
Good luck!
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iam doing project on vehical detection during night,fog,rain,&other environmental conditions so plese hep me to do this project ;
And any one plese send me source code for night time vehical detection
Matlab has an inbuilt function to remove haze: imreducehaze
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The interest is to understand what are the perspectives of bio or nature inspired methods for matching the signs of intrusuions.
Deeplearning approach can be great for future IDS. In general, IDS should be approached from a big data perspective.
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Could you pls let me know how we can determin Vit D3 on paper base technique ?
I mean how we can load the antibody on it and how that solution run to detect the vit D3 on band? Their are vitamin D3 detection KIT are available, how accurate are they ?
Pls guide me in this.
Dear colleague,
Probably you mean the lateral flow immunochromatography slide tests, when you mention paper based techniques. The priciples are explained at the website https://www.abingdonhealth.com/contract-services/what-is-a-lateral-flow-immunoassay/
Concerning vitamin D3 or a D2 I know only only slide test that performs close to the usual testkit on the clinical laboratory analysers. I have tested it myselve and saw their EQAS results. I could bring you in contact with the supplier if you want me to.
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A computer disc drive mfg. company had a problem similar to this irregular heart beat problem, 1985. The disc drive model consisted of 3 modified Lorentz functions. The model was tried on 200 drives; 199 drives agreed with a small standard deviation. But, the last drive showed a -major- defective drive. Thus solving a mfg. problem with a least-square curve fit. So, it can be done ... try it!
This is a typical anomaly detection problem.
We've found great success in using Machine Learning tools such as Recurrent Neural Network (RNN) adopting the Long Short Term Memory(LSTM) algorithm. We've demonstrated its sensitivity and diversity on different kinds of heart diseases. We also found great application of the same methodology in other domain disciplines such as predicting and detecting anomaly in jet engines and oil rig machinery offline as well as real time.
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The employment of machine learning in security field is higly emarged in the current era. But, yet, did the researchers in security field utilize from it in 100% detection or protection from one or multiple kind of malwares ? Or do you forsee that malwares ( or specific malware type, like ransomware or trojan or ... ) will be obsolete due to the successful analysis of their behavior (Dynamic or static ?) by machine learning algorithims ?
(Resources that support your opinions will be much supportive!)
When creating a malware, the creator has to think about malware-detection method first (otherwise his malware did nothing). => he created a malware that is not detectable with the current algorithms (anti-virus program). When a computer is infected, the defender analyzed the malware and creates a new mechanism to detect it. And again, the creator knows this mechanism and thinking of new malware. This cycle never ends, the battle between white hat and black hat hackers I would say
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Hi I am Wini a Masters student from Hochschule Anhalt. I'm really interested in AAV-9 production. I am just starting, and was wondering if anyone could provide me with some tips/protocols/techniques about AAV-9 vector Purification methods and detection of AAV9 ?
Since I have seen the production process also need helper plasmid or helper vector can anyone also suggest me which can be a best helper plasmids?
Hi Yesaswini, we have rich experience in the production of AAV with different serotypes. You could find a lot of information and protocol about on this website: www.genemedi.net/i/aav-packaging
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IL-1B/IL-18 secretion, westen blot analysis of 2 subunits of caspase-1, FAM-FLICA detection or another method?
You can also make extracts of your cells (all at the same cell "concentration") in an appropriate buffer (acidic pH) and measure cleavage of a caspase-1 specific substrate ( Amino Acid Sequence Ac-Trp-Val-Ala-Asp-pNA) in the presence and absence of a caspase-1 inhibitor. This would be the most sensitive method.
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I want to detect caspase 1 activation in human monocytes-derived dendritic cells after interaction with my pathogen.
It is best to have multiple lines of assessment- WB, IF (FLICA) and cytokine release provide corroborative evidence and more likely than not, the reviewers would expect you to have more than one assay.
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I performed 3 WBs for 2 groups of samples (first group twice). I used RAW 264.7 cells trated with LPS.
My first group of samples had a lot of unspecific bands, one of them was also IRF3, but there was too much of those unspecific. So I performed 2 more repetitions where:
• samples from the first group for phospho proteins had no bands and whole membrane glowed (I did blocking in milk) and for total proteins there was literally nothing to see.
• second group of samples had barely some bands for total proteins but no bands for phospho proteins with whole glowing membrane again. I used milk for primary antiobodies (total 1:200 mouse, phospho 1:1000 rabbit). I would appreciate any recommendation how to get better results and to avoid unnecessary mistakes.
A description of your current protocol would help. How and when do you lyse your cells? What lysis buffer are you using and how are the lysates stored? What antibodies and buffers/reagents are you using?
We used to do LPS stimulations of innate immune cells and then look at various cell signalling pathways. In our experience, it is best to do a kinetic study concentrating on the first 6 hours following the addition of LPS. If you go in later, you may not see phosphorylation. We used to lyse our samples in Laemmli buffer. But RIPA buffer + protease inhibitors should work just the same. Once lysed, store the lysates at -20°C.
From what you describe, you have a problem with your blocking too. Try using BSA instead of milk for blocking as well as for diluting your antibodies. Some antibodies cross react with casein in the milk and can lead to the whole membrane glowing when you add the substrate. Also what antibodies are you using? We recommend using antibodies from Cell Signaling. Probe the membrane with the phospho-Ab first, strip it and then probe with the total Ab.
So to sum up, make sure you are analysing the signal early enough, you are lysing your cells correctly, are using the right antibodies and use BSA instead of milk.
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Can anyone point me to an algorithm or a model that can detect body movement from the accelerometer data on a wristband.
I suspect that your question is too general. My wrist movement is somewhat independent of my body movement. For example, I may be playing a guitar and so my wrist will be moving in a certain manner. However, while playing the guitar I may be either, sitting down, standing up, walking or dancing to the music that I am playing. From this you can see that my wrist movements do not define my body movements and so one can not be inferred from the other.
Another situation where this "confusion" occurs can be manufactured if you have a chair that rotates. You can then sit in the chair with your wrist still while a friend quickly rotates the chair and (if you don't get dizzy) then if you look at the reading from your wrist sensor you will see that it seems to indicate that the wrist is moving (and it is but so is your whole body) and so you can not assume that a movement registered at the wrist only comes from the wrist.
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Hi, I'm doing doing RT-PCR to detect the presence (or not) of a pathogen. I've done it 6 six without any problems, however, my last three attempts failed, because I don't get a standard curve anymore.
The samples and the standards start in a low concentration, then they are simply not detected anymore (there is a gap in the graphic), and in the end they are detected again, but no signal of the standard curve.
I've already changed the standard dillutions (0,1; 1; 10; 100), the probe and the TaqMan, but nothing worked.
Is it possible that I'm mishandling it or it is likely a problem from one of the reagents?
Thanks!
This might be typically a problem of a wrong base line correction and a very low signal after amplification. As you can see the baseline fluorescence at cycle 1 is higher than yor plateau. This must differ at least one log scale; the plateau being 1 log higher. My first advice with respect to the baseline would be to set the cycles for baseline correction manually after e.g. cycle 6-8, or even later.
However, if you say that this is your normal control something must be really wrong. These curves really look like 'no amplification'. But first try to 'play' with the baseline correction. If this will not ameliorate your curves, you must indeed think of a damaged positive control (standard). The moreover you did change primers and probes. This can be simply tested I hope.
The other problem might be that your Taq polymerase is damaged; but I think thats unlikely.
So, one technical question. What is the signal and how does the amplification curve of your internal amplification (process) control looks like, or don't you use an internal control in you standards? I would strongly advice this in any case.
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I want to track only a single object , I want the RGB values of that portion in color frame. Any kind of suggestions is appreciated.
Hi Siddharth,
You got that right we are using a Background Subtraction Model , but a sophisticated one , combined with Wronskian Framework. This model was proposed by our Professor last year in " Gaussian Mixture Model Integrated with a Wronskian Framework for Local Change Detection in Underwater Video" research paper. Ya we are using pixel-level information to track our object of interest. This model can detect the stationary objects too, actually our model has two stages , first it takes some initial frames for background construction (we take such frames , where there is no movement), than comes the object detection stage , than we take frames of moving objects , to detect. Yup ,it will definitely fail if there is lighting variations . We will work on that in near future. I have already implemented (HOG+SVM) Framework + our Background Subtraction Algorithm , got false positive results in some frames . Thanks for a response.
- Sophomore student
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I am planning experiments which should produce formaldehyde and I aim to quantify it. The amount generated will be small (upper nano to micromolar range). Ideally, I'd like to use tests that wouldn't involve long/complex sample manipulation, such as chemical derivatisation.
I am aware of many methods to quantify formaldehyde (e.g. PFBOA derivatisation), but is there any certified methods that don't involve derivatisation?
I am aware of some types of spectroscopy (e.g. Raman) being used for such intents, but as far as I am aware, their sensitivities are pretty poor.
Any ideas?
We used the DNPH method at UCL, it works well and is quite simple if I remember. You could try adding potassium ferricyanide solution to a sample and running NMR as it chelates the Fe but not sure about the Ni. May be worth a try perhaps.
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to detect cases that condemnation carcass after slaughter
TB.......... if confirmed........ can reach and be found in any part of the body
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We are working on a pedestrian tracking project. We don't need a long-term tracking the tracking manly required to determine the direction of those people. Now, suppose that i have two types of video recording; one is a top view, and the other is with an angle; which one is easier to deal with, in term of the algorithms? And the accuracy of those algorithms?
Top view will generally be easier insofar as:
1. the viewing angle is perpendicular to the horizontal plane in which people are walking, giving good information about position in the horizontal plane;
2. there are no occlusions (underpasses, tree foliage, balconies that people can walk under, partially or totally blocking them from view at times;
3. there is consistent high contrast and low shadows from top-down lighting;
4. people keep a comfortable distance between themselves.
An angle view will be worse insofar as:
1. a low viewing angle generally loses information about distance along the line of sight;
2. there are occluding walls or signs, and insofar as one person occludes another in passing;
3. a crowd of many people of different size creates a continually changing, often low-contrast, background for a tracked individual.
If you had people who are strangers to each other (well separated), walking civilly on a uniformly illuminated white sidewalk with no overhead occlusions, then the tracking algorithm would be trivial. Any reasonable algorithm would perform reasonably well because contrast is high and confusables are few. This would not be true if you viewed the scene from a low angle.
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I combined  QCM  with loop-mediated isothermal amplification (LAMP) for the detection of specific DNA. But the false positive result is big problem. Can anyone help solving this problem?
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It's often a bigger challenge to differentiate drones with bigger birds from radar data. Amidst the presence of some techniques using video detection, radio signal detection, heat signature detection and the radar based approach, the effectivity of the technique is not very well placed. Would you please help me with some directions, as I am interested to work on this topic.
Depending on the desired detection range, and available range and azimuth resolution, micro-Doppler signature might also help in differentiating UAVs from birds.
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Dear All,
How do i decide which QD to purchase? and does the emissison peak matter if i am only aiming for detection and not illumination purposes?
what are the pieces of information that i should look for when making the purchase?
PbS QD is the most promising materials for optoelectronics application.
The synthesis of this PbS QD is quite easy. You can read this paper (DOI: 10.1002/adma.200305395)
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Im looking for the newest hybrid metaheuristic technique to use it over  NSL data-set or any other DDoS datasets
You can apply quantum inspired swarm intelligence. Since quantum based applications are multi-faced in nature, the algorithm can cover multi-modal aspect of intrusion. Quantum PSO can be one suitable approach. You can also substantiate the proposal with some mathematical convergence proofs. You can refer to an article on Evolutionary PSO.
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Can anyone please explain about the working of thermal imaging and UV imaging? How these modalities useful in detecting the ingredients from food?
Thank you.
UV and IR camera allows to measure intensity of photons flow at this wavelength.
You can,t chracterize food using thos 2 wavelength. You need spectro analysis and create solution of food
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How to detect bad data in inputs of system dynamic equations?
Dear Mr. Bhui,
You can still detect any kind of faulty input to the UKF system equations using the innovation sequence and an appropriate chi-square test applied to the innovation covariance of the filter.
For such detection your filter must be sensitive to the faults in the inputs (e.g. a filter with low process noise covariance, Q).
If there is a possibility for both measurement and input faults then you may need also a fault isolation process as you need to detect two types of faults both from the innovatiaon sequence. I suggest you to check the following publication in this case for the details of a fault isolation process
We applied the same isolation process for an estimation problem with the UKF in
If you have trouble accessing the full texts I can send them via e-mail.
Best regards
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Topic  fault detection in coal seam
You might try Geogiga software, made for shallow exploration. One month free trial and not expensive to buy. Runs on Windows.
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I'm looking into sulfur (elementary, H2S production through wild yeast strains, sulfite, etc.) in grape must. Would anyone know material about the possible quantities that can be found, and by which ways sulfur is detected in labs?
Definitely take a look at the articles by Alexey Kamyshny, for using HPLC methods to characterize sulfur species. Sulfides can be easily measured using the methylene blue method (there are many colorimetric kits for doing this), though there are also good sensors out there for sulfide measurement as well. There are test kits for sulfite on the market, some of which are specifically intended for wine making. Measuring elemental sulfur can be a little more tricky. Voltammetry can be used to detect various sulfur species, including elemental sulfur. I've used x-ray absorption spectroscopy and Raman spectroscopy to detect elemental sulfur in my samples, though I wasn't intending quantification through those methods.
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We know that the major problem in wireless communication hidden node problem. I need help about the algorithms to detect hidden node problems
I experienced 2 approach for the solution :
- Radio manifacturer proprietary protocols used to implement a token passing based protocol, where the unit of time is divided by the # of active connected clients (TDMA), then each one has a time slot to transmit in. No starvation but latency introduced. A practical implementation (currently working on field ) is NV2 protocol that can be enabled on Mikrotik radio devices.
- Indirect approach based on measuring the whole link usage assigned to the AP slowing down the usage of the nodes currently occupying the biggest % of the assigned badnwidth. Slowing down the node generating the biggest  flows will give to the other transmitting node the possibility to increase and improve transmission. The process is iterated to converge to the equalizing solution. This approach has the advantage to NOT require any proprietary protocol implementation neither any 802.1 modification becasue it's implementation indirectly regulate channel usage policy
Here a practical implementation of this concept:
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Dear all
I would like to know how can I measure Arginase I activity/NO concentrations in heart samples. Please, suggest me the best way to do so,
HR
hola Hector, tengo un paper de 1944 de jbc, pero medicion de arginasa, espero te sirva, saludos!
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to detect change in milk after treatment by thermal method
Multiple issues are related with heat treatment of milk. It depends on the type of protein and the range of heat treatment with the time of treatment.
In lab condition, it is also important to see the come-up time of steady-state temperature while doing the thermal treatments as it needs to be as quick as possible.
The following papers might be a good start to make a work plan-
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Im going to do Multiplex qPCR for detecting 3 viruses, how i calculate a valid t sample size for testing
Please consult Marketing Research books by any of following authors:
Andy Field
Naresh Malhotra
Hair et al.
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After assembling the coin cell (half cell), is there a way to detect/ predict the bad cell without charging the cell? So that we can reduce the possibility of coin cell getting explode during charging/discharging test or while performing CV.
Thank you all for your time.
Upon charging/discharging CV tests of your Na half cell, then you increase the percentage of the nanosize Na-clusters in the Na negative electrode. Initially, in your Na half cell, the melting temperature of the Na bulk material is not dependent on its size (97.8°C :  bulk Na). However, as the dimensions of a material decrease towards the atomic scale, the melting temperature scales with the material dimensions. The decrease in melting temperature can be on the order of tens to hundreds of degrees for metals with nanometer dimensions. So, upon CV cycling tests of your Na half cell, then the nanosize Na-clusters increases to a high percentage; and a nanosize-Na melting might occur at a much lower temperature (<97.8°C); then a Na-nano-metallic short circuit (SC) can take place (synergy by gravity for Button Cells, also) at a high cycling number Ncritical, while performing CV.
In short, a SC risk scales with the cycling number N.
Also, such a SC risk might be a major security issue (risk for fire : N>Ncritical) for a high power application (for EVs etc.).
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i want to know the light microscopically differences between apoptosis and necrosis,
Use Apoptotic kit and see nuclear staining. Sometimes late apoptosis is similar to necrosis,but early apoptosis is condensed nuclear chromatin sometimes  half-moon-shape. If you are able to perform semithin sections embedded in epoxy resin apoptotic pictures are fantastic!
Good work!
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my thesis is intrusion detection using HMM. but percent U2R is the best 95%
tell me why?
Look the link, maybe useful.
Regards, Shafagat
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I'm trying to detect IL-8 in A549 cells, the problem is that the all the samples, incuding the negative controls (which are only with PBS) are so stimmulated that I have saturation of the wells. Anybody have had this problem or something simmilar?
Thank you!
Thanks Rafael, I will try that!
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Is it completely data driven failure detection??? Which type of process or system is being considered?
Sir, could you please clarify the question littlebit more. Not getting propely i.e which context? Failure of what material mmc or d2?
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For instance, how we generate an accurate results of detecting occlusion in a sequence of images in real time ?
Hello,
For the detection of occlusion, i think that the tracking of the different object in motion is an accurate process and it doesn not rely on any a priori assumptions. Indeed, it is an automatic process.
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to detect the factors that accelerate the occurrence of rigor mortis
agreed with mushtaq ahmad
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I was trying to assess Arhaea in my sample but the results are very low (8*10^0, 1,7*10^2). I am wondering whether this result should be recognized as "not detected" or not.
Hi Josep
Is very large to respond, however I'll link some references
How was your definition of detection obtained?
- inspired by the ISO 7218, point 10.3.2.4.1,
How do you incorporate PCR efficiency,
the DNA purification procedure and the efficiency of bacteria recovery in your determination of detection limit?
- it must to be experimentally evaluated or using internal standards
How do you ensure your PCR setup is appropriate to apply the detection limit?
- it mus be done during the method validation
How do I calculate the detection limit in qPCR?. Available from:
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Is there some trick in determining if a buffer contains calcium? Preferbly without having to order some kit since time is of the essence
Hi Anna, if you want to go "old school" in determining Ca++ in your solutions, then you can use Ksp for Ca++ solubility with various anions:
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I have ndvi values from series of points obtained from time series satellite images. How can i detect anomally from these values? Thanks
Ok thank you very much Sir for the help
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Agrobacterium-mediated transient expression of a candidate protein induces strong cell death in Nicotiana benthamiana leaves. There is a FLAG taq in the N-terminal. But, I can not detect it using western blot. What can I do? Looking forward to anwsers...
Is your candidate protein a soluble protein? You might have an issue seeing the protein on a western blot if the candidate protein is localized to the plasma membrane or the ER or maybe even the chloroplast. I would try adding 1 - 0.1% Triton x-100. It increases the overall amount of protein I'm able to see on my westerns. If it is localized to a membrane you might want to try ultra-centrifugation techniques to enrich. I haven't extracted from N.benthamiana but I have extracted lots of protein from Arabidopsis.
Also, worst case scenario, your flag tag is cleaved or not there. Have you checked the cDNA? Good luck!
Here's a publication example of extracting proteins that cause cell death in N.benthamiana. Maybe their protocol is different from yours. http://www.sciencedirect.com/science/article/pii/S1674205214600733
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Are there any publicly available real database activity logs for misuse/anomaly/insider threats detection ?
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Red maleimde protocol
Thank you Christian Marvelous, I have this article but I'm looking for detailed procedure/steps
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Does anybody knowing what sort of techniques/ methods can be used to detect MicroRNA
Hi Mohamed,
There are four main methods, they are microarray, nCounter (NanoString), NGS and qPCR. Microarrays are good for throughput, but lack dynamic range and so accuracy, nCounter is more accurate, but lacks throughput and sensitivity at the lower end. NGS allows discovery of novel miRNAs, but is expensive and require the most data analysis. qPCR is medium price, fast, very accurate but has a medium throughput. The choice of method therefore depends on what you wish  to achieve, what sensitivity you need and how much you are wanting to pay for this.
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What is the best compound / marker  in order to determine the void volume (V0)  of a Shodex Sugar SP081 column (SEC and LEC column, RI detection)? Thanks for your advices!
Dear Greg, thank you very much - I´ll try one of those large polymers!
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I used ESI-QTof-MS to identify the adducts formed between phenolics and amino acids and i used Nigative mode. My question is: why my adducts m/z have higher mass than normal? For example, my adduct should be m/s 420.1 but 421.2 was detected.
Thanks so much for your interest. I want to inform you that my sample was directely injected into ESI-QToF mass spectrometer via a syringe pump and many isotopes for each adduct were appeared.
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In TamilNadu, Which institute is carried out these experiments?
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I want to know the procedure of the method of the detection of Cr. using Diphenyl Carbazide.
Check the APHA 'Standard Methods of Water and Wastewater'.
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i want to study and do research about mycovirus, but i don't know much about that. Anyone can help me? thanks
You most welcome
Houda
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In case the answer is positive, please share what kind of images and methodology.
I am sorry, my research is lactic acid fermentation of fruit and vegetable.
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I want to improve the THD method in detection of islanding detection, so I won't use a new parameter like H that use in the attached paper, it proposes a grid voltage of 0.38 kV and 100kW that is connected to 13.8 kV, so I need to set a threshold for H parameter, could you help me and tell how dose it chooses?
consider then ratio of 13.8/0.38 . Multiply this value with the existing value of H. that value of H may help you in your design.
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Dear Alls,
I got the problem on my qRT-PCR as I could detect GAPDH expression but I could not detect specific genes. I already checked primers and repeated but the results still failed. Do you have any suggestion? Thank you.
Hi Sarocha,
You might consider the following points for trouble shooting,
1. check your primers again, like do a BLAST with your gene sequence and check , check the Tm ( gradient PCR) , self complementary nature of the primers or if the primers are forming hairpin.
You should also consider the stability of the gene transcript that you are trying to quantify.
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Specially after certain treatment during in-vitro study
In many cases, it is possible to perform an ELISA to measure the amount of the protein thanks to the commercial availability of antibodies and sometimes whole kits.
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If the compound to be detected is being run in HPLC, is it necessary to prepare that particular compound with the mobile phase??
No, it is not.  But it is to good practice to prepare the sample with mobile phase, the baseline will be cleanner.
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I'm uncertain if it's a technical issue that I need to troubleshoot and resolve.
PMA and ionomycin, at optimal concentrations, should stimulate all antigen specific cells in a mixed population. A frequently overlooked problem with these agents is that they do not function through the T cell receptor. They are able to induce cytokines previously made by anergic T cells and therefore can give a spurious readout of cytokine production from antigen-specific cells. This is explained in:  Gabrysova, L., et al. Journal of Experimental Medicine (2009) 206: 1755-1767
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Sudden Oak currently is important issue in forests of Iran. I want detect this issue using SAR data.
Yes, you can do with the help of GIS together.
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