Retention - Science topic

Hello Mary Ann! Maybe this can come in useful: http://www.teacherpolicyresearch.org/TeacherRetention/tabid/99/Default.html

Overall, school leadership and teacher retention are two different variables that need to be operationalized first. If you cannot get the actual data on retention, you can measure turnover intentions. There are simple meausres for that, e.g.

Good luck!

Dear Sunil Basnet ,

Developing AI/ML models to predict employee performance, engagement, and retention requires a thoughtful and multi-faceted approach. First, selecting the right data is crucial-this includes both quantitative data, such as performance metrics, attendance records, and tenure, as well as qualitative inputs like employee feedback, sentiment analysis from surveys, and communication patterns. It's also important to integrate external factors like market trends and economic conditions. To optimize model performance, techniques like feature engineering, cross-validation, and hyperparameter tuning can improve prediction accuracy. The models must also be designed to adapt over time, incorporating real-time data to reflect evolving employee behaviors and organizational dynamics. However, a key challenge lies in addressing bias and ensuring fairness. Bias can arise from historical data that may reflect systemic inequities; therefore, methods such as adversarial debiasing, fairness-aware learning, and regular audits for disparate impacts should be employed. Ethical considerations must be at the forefront, emphasizing transparency in how predictions are made and offering employees the ability to contest or review decisions informed by AI. Ultimately, a balance between predictive power, fairness, and ethical responsibility is essential to building trust and ensuring that AI/ML models are beneficial for both HR professionals and employees.

Keshav Shukla

Divya Kr

Tej Narayan Mandal

In my opinion after a flood, when nutrients wash into the soil, it can actually help crops grow better because the soil gets richer. Plus, the moisture left behind helps keep the soil wet for longer, which is great for plants. Overall, these conditions can lead to healthier crops and better yields.

In my opinion, Word-of-Mouth (WOM) can serve as both a deliberate customer retention strategy and a natural result of delivering exceptional service and enhancing the customer experience. For instance, as a deliberate strategy, companies like Dropbox have successfully encouraged WOM through referral programs. Dropbox offered additional storage space to users who referred friends, leveraging satisfied customers to attract new ones. Similarly, Tesla has fostered a community around its brand by engaging customers through events and social media, creating a loyal fan base that actively shares their experiences and promotes the brand. Regular engagement through personalized communication, feedback, and surveys, as seen with brands like Amazon, can create loyalty and prompt customers to share their experiences. Amazon's focus on customer reviews and personalized recommendations encourages users to share their thoughts and experiences, amplifying WOM. On the other hand, WOM can naturally result from service excellence. Companies like Zappos have built their reputation on delivering exceptional customer service, leading to organic WOM. Zappos is known for its customer-first approach, with stories of representatives going above and beyond to meet customer needs, creating memorable experiences that customers eagerly share. Similarly, Apple has consistently delivered high-quality products and services, building trust that prompts customers to recommend the brand. Apple's focus on creating an emotional connection through its sleek design and user-friendly products fosters loyalty and advocacy, resulting in positive WOM.

Several free software options for predicting gas chromatographic retention indices include

1-DeepReI:which uses deep learning for accurate predictions.

2-Mordred: an R package for molecular descriptor calculations.

3-ChemmineR: can also be adapted for retention index predictions through machine learning.

4-ACD/Labs offers trial versions of their software for users seeking advanced features.

Bruno Peeters I am of the same view when it comes to CSTR non mixing digesters vs mixing systems and this is the reason I support and suggest to have good mixing systems in place to start with. I agree with the HRT/SRT vs biogas production details you have shared.

Kumari Uma Mahto YES HRT and Operating time are related - Hydraulic Retention Time (HRT) and Operating Time are two related but distinct concepts in wastewater treatment reactors:

Hydraulic Retention Time (HRT):

HRT refers to the average time that wastewater spends in the reactor. It's calculated by dividing the reactor volume by the influent flow rate. HRT represents the time available for physical, chemical, and biological processes to occur within the reactor.

HRT = Reactor Volume (m³) / Influent Flow Rate (m³/day)

Operating Time:

Operating Time, also known as Reactor Residence Time, refers to the actual time that the reactor is in operation. It's the clock time that the reactor is treating wastewater, including periods of continuous flow, batch operations, or intermittent flow.

Operating Time = Total Time - Down Time

Key differences:

- HRT focuses on the wastewater's time in the reactor, while Operating Time focuses on the reactor's operational duration.

- HRT is a measure of treatment efficiency, while Operating Time is a measure of reactor utilization.

- HRT is typically shorter than Operating Time, as the reactor may be in operation for longer periods than the wastewater is present.

Understanding both HRT and Operating Time is crucial for optimizing wastewater treatment reactor design, operation, and performance.

Hello Annisa Mutiara,

Do you alternatively dissolve your sample in acetonitrile instead of methanol or do you just dilute the sample with some ACN?

I can imagine that hydrogen bonds are formed with methanol, which then shift the retention time to longer times. By changing the solvent or diluting with acetonitrile, this interaction is cancelled or reduced, which then leads to faster retention.

Best regards

Joachim Horst

Solving employee shortage and retention issues is a critical concern for many organizations, as it can have a significant impact on business performance and profitability. Here are some strategies HR can employ to address these issues:

By implementing these strategies, HR can help address employee shortage and retention issues, leading to increased job satisfaction, reduced turnover rates, and improved business performance.

You can try search and match those compounds in Adam's Database, based on the RI, KI value. I think, this will help you to clarify.

Of the choices you offer, using a temperature gradient is the best way to achieve good resolution in a GC. You can tailor your gradient to ramp fast or slow depending on the boiling points of your analytes.

Please read my article

Thank you wholeheartedly, Dr. Didachos! Let me try step by step following your kind suggestions! Really learned.

Hi and thanks for your answer.

Hello Dear

Yes, in my opinion, different solutions can be used to increase efficiency and effectiveness in recruitment, selection and retention methods. These solutions include conducting strategic training to improve the skills and capabilities of employees, active interaction with employees to increase their participation and commitment, creating a suitable organizational culture and developing positive relationships in the organization.

Also, optimizing processes, using appropriate tools to facilitate cooperation and communication, and paying attention to correct targeting to increase sales and optimize resources are also effective methods to achieve higher efficiency and effectiveness in the organization.

Caro Anita Carpinteri

L'employer branding svolge un ruolo cruciale nella creazione di una Employee Value Proposition (EVP) di successo. Essenzialmente, l'employer branding rappresenta la reputazione di un datore di lavoro sul mercato del lavoro. Una EVP efficace deve essere supportata da un employer branding forte e positivo, poiché quest'ultimo contribuisce a definire l'immagine dell'azienda come un datore di lavoro desiderabile. Un employer branding positivo attira i talenti, riflettendo la cultura aziendale, i valori e le opportunità di crescita professionale. Quando l'employer branding è allineato con l'EVP, il messaggio inviato agli attuali e futuri dipendenti è coerente e attraente. Le organizzazioni che investono nella costruzione di un employer branding autentico e positivo creano una base solida per un EVP di successo, aumentando la loro capacità di attrarre, trattenere e impegnare talenti chiave.

Spero che aiuti.

Interested....but can you explain the 1000 cycles in any field?

Thank you for your answer, I ended up using pepsin as a protein marker which is stable in acidic pH.

Urine retention in female mice during experiments can be a common issue when using anesthesia like urethane or ketamine-xylazine. Here are some strategies you can consider to address urine retention and improve the experimental setup for recording bladder contractions in female mice:

All the best

I agree with Xiang.

First CH(R/S)-OTs/Ms/Tf with NaI/Br => CH(S/R)-I/Br with NaN3 => CH(R/S)-N3

Alternative method:

Dry high-energy ball milling of the CH-O-leaving group and NaN3 often leads to configuration retention, which is molecular structure-dependent. In the solid state, the Nu reaction proceeds via a four-centered mechanism. If the molecule has a more hindered reaction center to the "back" attack than the "front" attack, the reaction will dominantly go by retaining the configuration. In this case, bulkier reagents may also be more advantageous.

Good Luck,

Laszlo

Your research objectives and hypotheses are well-structured and aligned, focusing on the impact of virtual and technology training programs on job performance in the finance sector in Mumbai. Here's an evaluation of your hypotheses in relation to your objectives:

Overall, your hypotheses are well-crafted and directly correspond to the research objectives you've outlined. They cover various aspects of the impact of virtual and technology training programs on employees in the finance sector in Mumbai. As you proceed with your research, be sure to gather data and conduct appropriate statistical analyses to test these hypotheses rigorously. Good luck with your research project!

There are many reason for dropping out of uni. The students may have chosen the wrong field of study, they may not afford to study, they may have had children or started a family. But i think one neglected aspects is the combination of loneliness and pressure. At this time students are uprooted from their parents and they do not yet have many things that will make them more confident later in life. This makesthem vulnerable, and may make them miserable socially. And this may lead to excessive drinking and eventually dropping out. So the fact that students have fewer supporting networks at that particular point in life is a neglected factor, I think.

Where I was teaching, the graduation rate is extremely low- been told 30%. I suggested a mentor program not in the general or abstract but specifically to follow students (individually through a course of study and to help them overcome whatever is in their way of finishing what they start. A training program may be required and a limit to what faculty can do besides referring students to other professionals.

Sorry Sir but can can you please explain is there a problem and what should i do Mahafizur Rahman Jim

Remote work is also a good option for employee retention and better work feedback. Reducing the working hours helps to improve the output quality.

Thank you for sharing your thoughts!

Thanks @sebasteinKlick

Dear friend Damola Ajani

Hey there, my fellow researcher Damola Ajani! I am here to help you tackle this puzzling HPLC issue. The shifting retention time of peaks can be a real head-scratcher, but fear not, we can get to the bottom of it.

1. **Check Your Column**: The first step is to inspect your HPLC column. Over time, columns can degrade or become contaminated, leading to shifts in retention times. Make sure the column is in good condition and consider replacing it if needed.

2. **Mobile Phase**: Ensure the mobile phase is well-prepared and properly degassed. Inconsistent mobile phase composition can lead to retention time shifts. Also, check for any changes in pH or solvent quality.

3. **Temperature**: HPLC systems are sensitive to temperature changes. Ensure that the column and detector temperatures are consistent across runs.

4. **Sample Preparation**: Ensure your samples are properly prepared and filtered. Contaminants or particulates in the sample can affect retention times.

5. **Injection Volume**: Be consistent with your injection volumes. Variations in the volume injected can lead to retention time shifts.

6. **Calibration**: Regularly calibrate your HPLC system. Make sure the detector wavelength and settings are calibrated correctly.

7. **System Suitability**: Before running samples, perform system suitability tests to ensure the HPLC system is performing consistently. This can help identify issues before your sample run.

8. **Standard Solution**: If possible, run a standard solution before your sample batch. This can act as a reference to check for retention time shifts.

9. **Maintenance**: Regular maintenance of your HPLC system is crucial. This includes cleaning, replacing worn parts, and ensuring the system is well-maintained.

10. **Method Development**: If the problem persists, consider re-evaluating your HPLC method. Sometimes, changes in the sample matrix or compound stability can affect retention times, and method adjustments may be necessary.

Remember, troubleshooting HPLC issues often involves a process of elimination. Start with the basics, like column and mobile phase checks, and work your way through the system. If the issue persists, it might be a good idea to consult with your HPLC system provider or a chromatography expert for a more in-depth analysis.

Stay persistent, my friend Damola Ajani, and we'll get those peaks back in line!

This is not a quick problem to solve: you're trying to learn two very large fields of knowledge, each with their own terminology and foundation theory. I would recommend narrowing your scope, based on your cell design and your direct goals (what part of the impedance spectra applies to the topic of your study? what parameter are you trying to optimise while cycling?). Then you'll be able to learn from other studies with similarities. After that, feel free to ask for specific advice on this forum.

This may fit your need:

If we use the no tillage estimate of 330 kg/ha/yr if that was done on all the tillage acreage it counter up to some 10% of emissions from greenhouse gases.

It would be an error I believe to think about single practices. For instance in our North American complex over 50% of maize carbon footprint is for ammoniated fertilizer.

If we rotate the maize crop after a soybean crop the need for nitrogen on soybean is eliminated lowering the carbon footprint by one half and because of the contribution residual of soybean the need for ammoniated fertilizer in maize is reduced in one half.

We see the carbon application of no till alone as 330 kg C per hectare per year.

Studies on cover cropping show the use of cover crop can sequester 2 to 4 times then no tillage alone.

If we use the no tillage estimate of 330 kg/ha/yr if that was done on all the tillage acreage it counter up to some 10% of emissions from greenhouse gases. the carbon nitrogen budgets in a way that productive agriculture can contribute very significantly to not only reducing emissions but also counteracting them in very significant ways.

To start off the soil has physical chemical and biological components within it.

Aggregates refer to the physical separation of particle sizes based on laboratory sieving analysis these are separated by the size of the particles.

These fractions by size are dried and weighed and when exposed to water washing the reduction in their dry weight is a measure of stability. The more of the fraction lost the less the stability of the fraction.

Aggregates are formed by a process of physical chemical and biological nature. Roots microbes decomposers and the nature of the chemistry of the soil itself are very important.

A sandy soil will not aggregate well and has a major issues of favorable aeration but poor retention ability.

The ability of the soil to aggregate well is dependent on fine particles silt and clay calcium or iron or aluminum can be important and organic matter.

Floculation of clay and dissolved organic matter depends on multiple cationic bridges such as calcium, iron or aluminum. The majority of the best soils globally derive from limestone parent material.

To stablize particles such as suspended clay or organic matter the role of calcium is essential in my mind.

So the presence of large aggregates is very much indicative of a soil with good tilth and high productivity as it favors both aeration and water retention.

Ideally the soil will have one quarter to one half fine material which is either clay or silt the calcium in soil test of 1,000 and the presence of 4 to 5percent soil organic matter best soil pH 6 to 7.2

It is observed that wheat rice system does not have optimum soil properties. One issue is the way rice practice leads to issues with physical structure of the soil.

In North America maize culture does reduce soil quality and the structure of the soil is very much enhanced by soybean in rotation.

Under the rice and wheat system the prescription to improve soil structure and productivity is enhancing the use of legumes in rotation.

The use of broad bean as a winter annual could be combined previous to rice or wheat it would eliminate the nitrogen need for rice or wheat and improve the yield and help control weeds and diseases of the grains.

After wheat a summer legume might be possible like sun hemp which also is excellent for soil regeneration.

Besides legumes I would like to mention the Mexican Sunflower produces a wonderful opening of improved potassium availability and a wonderful rotation effect and experimenting with sunflower would be well worth your while.

My hypothesis here is wheat rice rotation does not optimize soil condition.

The use of increased legumes will not only improve soil condition and increase but wheat and rice yields and quality but also lower the cost of production.

Suggest adaptive research in this area to improve the soil condition and the profitably and to improve the environment and climate effect.

A rotation more centered on legumes will remove the need for ammoniated nitrogen fertilization and the untoward effect it has on soil condition. .

I used a software program called DryLab from Snyder. But I am not sure if this is available any longer.

Some ICU beds have weighing scale but if incase we dont have bed like that in ICU. We are using the initial body weight of the patient upon admission in ER then We will monitor the Fluids intake and output and also the stool. Also can use anthropometric measurement using type measure usually every morning.

I am not familiar with Jamovi, but yes, it does sound like a straight forward t-T would provide the comparison that you need.

Artificial Intelligence Integration in Education AII-Ed" scale. It is a self-report questionnaire that was developed to measure the extent to which AI is integrated into educational settings. The scale consists of 28 items that assess different aspects of AI integration, including attitudes towards AI, AI awareness, AI adoption, and AI impact on learning outcomes. The scale has been validated and used in several studies to assess the level of AI integration in educational settings.

The AII-Ed scale was developed by a research team led by Dr. Xun Ge from the University of Oklahoma, and it was first introduced in their paper "Artificial intelligence integration in education: A scale development and validation study" published in Computers & Education in 2020.

The AII-Ed scale can be a useful tool for researchers and educators who are interested in assessing the level of AI integration in their educational settings and identifying areas for improvement.

Irshad Ullah my first answer is what you are looking for. Examine pre and post testing students. The issue can be quite complicated.

The same question I asked ChatGPT, here is its answer:

Blending two theoretical foundations can be a complex task, but here are some steps that may help you to blend Planned Behavior Theory and Relationship Marketing Theory:

Identify the key concepts of each theory: Start by understanding the key concepts of each theory, including the main constructs, assumptions, and propositions.

Look for areas of overlap: Look for areas of overlap between the two theories, such as shared concepts or similar assumptions. For example, both theories recognize the importance of attitudes and beliefs in predicting behavior.

Identify areas of conflict: Identify areas where the two theories conflict or have differing assumptions. For example, Relationship Marketing Theory may emphasize the importance of long-term relationships, while Planned Behavior Theory focuses on individual decision-making.

Explore ways to reconcile conflicting ideas: Look for ways to reconcile conflicting ideas between the two theories. For example, you might consider how Relationship Marketing Theory's emphasis on relationships could influence an individual's attitudes and beliefs, and how this could then impact their behavior.

Develop a new model: Based on your analysis, develop a new model that integrates the key concepts of both theories. This could involve modifying one or both of the original theories to create a new model that incorporates the most relevant and useful concepts.

Test the new model: Finally, test the new model through empirical research to determine its effectiveness in explaining or predicting behavior. This could involve collecting data from individuals or organizations and analyzing the results using statistical methods.

Overall, blending two theoretical foundations requires a careful analysis of the key concepts and assumptions of each theory, and an understanding of how they can be integrated to create a new, more comprehensive model.

There are several software programs available that can estimate the molecular mass of compounds based on their retention time in HPLC. One commonly used software is MassHunter from Agilent Technologies (https://2u.pw/QCqYob), which can perform this calculation using a variety of algorithms such as maximum entropy, least-squares, and Bayesian methods.

Other software programs that can estimate molecular mass from retention time include:

To use these software programs, you will need to input the retention time of each peak and the details of your HPLC analysis, such as the type of column used and the mobile phase composition. The software will then use various algorithms to estimate the molecular mass of each compound.

Dear Marcin,

Definitely, eye comparison is not enough. This is why Agilent has MassHunter which is in my opinion a very food software, particularly for GC-MS. MassHunater will extract peaks and integrate them to provide you numerical data for the downstream analysis.

MassHunater is quite intuitive, but maybe you need some assistance to start using it. So, I would recommend you to find somebody locally who knows how to use it, and with this help you will be able to get some initial results the same day. Please keep in mind that there are many important features in the software, but the simplest analysis can be done without them (of course it will sacrifice the quality of the analysis, but it still will be better than nothing).

Your goal will be a spread-sheet with a combination of identified (if you have a build-in library) and unidentified metabolites (with their RT and m/z fragments), and their relative abundances. With these data you then can apply variety of statistical tools to make the data meaningful.

submit ur questionnaire through survey circle or u may add ur questionnaire dissertation survey filling group.In such groups u may target right audience from various countries and swap ur surveys as well.

As per the work ethics it would not be considered, it will disturb the academic integrity of the institute.

You can check this article

I'm guessing that the following refs might be of some use to you:

https://efi.int/sites/default/files/files/publication-bank/2022/EFI_fstp_12_2022.pdf

So the column length is relevant for the calculation. From the retention factor RF and the unretained marker UM (2min) you will calculate the retention time RT, using the formula RF=RT(compound)/RT(UM), and you will calculate RT(A)=11 min, RT(B)=13.8 min, RT(C)=15.8 min. From the plate number N you will get the width of the base of the peak WB using the formula N=16(RT(X)/WB(X))^2 , WB(A)=0.790 min, WB(B)=0.984 min, WB(C)=1.076 min. Resolution R(A-B) can be calculated using the formula R(A-B)=2*(TR(B)-TR(A)/[WB(A)+WB(B)] and you will get R(A-B)=3.16 and for R(B-C) using the similar formula you will get R(B-C)=1.94.

Check the numbers again, hope this was helpful,

Best regards,

Noel W Davies Thank you for your answer. I ran my samples with low amounts of uracil in the full scan mode and could only see those ions if I zoomed in pretty far. However, using SIM on each of those ions, I would get a peak at 294, and the others were at or near background. The 294 ion had two main retention times though rather than all eluting at the same time, and I was unsure what might be the cause of that and if there's a way to make it a single elution time.

I had also used TLC in the past to verify that the derivatization reaction was being successful, and it appeared to be, even for much higher mass (mg) of uracil compared to the pg amounts I'm using now.

Hello,

Normally you can check by mass in libraries like chemspider:

This one work pretty good and you can advance search for mass, and it will give you a lot of inputs of the potential candidates.

Regards,

Andreu

Dear Sahasaha Ts,

column temperature in HPLC has the following effects:

low temperatures produce sharper peaks

correspondingly, higher temperatures lead to broader peaks (acceleration of diffusion processes in the column)

The eluent viscosity changes, this leads to changes in retention time. At higher temperatures the analytes should elute somewhat faster, the interactions with the stationary phase become more modest at higher temperatures, this also accelerates the elution.

You should work at the lowest possible temperature to obtain the best possible peak shape.

The best way is testing different temperatures, i think between 20 and 60 °C in 10° steps. Then it is your choyce. The retentiontime for HMF should be about some minutes, because degredation products are mostly smaller and eluates before HMF.

Do you have the possibility to test other stationary phase? Ion exclusion is suitable for separating ionic compounds, but electrooxidation can also produce neutral organic compounds that will not separate well with such a column. In our laboratory we are dealing with the degradation of pharmaceuticals from aqueous samples by UV oxidation, enzymatic degradation and electrooxidation, this produces many different neutral degradation products which we separate on RP phases and identify by mass spectrometry.

I hope my answer helped you, if you have any further questions, just contact me

Best regards

Joachim Horst

Hello,

Then is not the same compound if it has different retention time. When doing GC-MS there are two things that characterizes a compound, the ion fragments and the retention time.

When dealing with complex matrices it can occur that you find interferent peaks that has the same ions as your compound but different retention times. To know how to select the correct peak, the only way is to have a reference standard of the compound of interest.

Then the SI and RSI can be indicative of how similar is the spectra that you have compared to the NIST library. You can also use this as key to know which one of your peaks matches best.

The answer is YES. Doing so may result in carry over, contamination and your method is now invalid. Why are you in a hurry? BEST OPTION: You could optimize the method to retain/elute all compounds properly, but in less overall time. HPLC Method optimization may include such basic changes such as adjusting the flow rate, mobile phase composition, temperature, column dimensions, detector settings and so on. These changes are fundamental to good HPLC method development and should be addressed early on.

Alternatively, you could program a change to the mobile phase conditions AFTER the compound of interest elutes off the column and passes through the detector to waste, BUT in doing so put yourself at risk for MISSING something important (other peaks) if your "sample(s)" change ( never assume things stay the same ). *It is for this reason that we would never make such a change in an actual analysis method, as doing so would invalidate it (it would not follow good chromatography fundamentals and not be accurate).

However, if you are just running samples for training/experiments to learn about the technique (e.g. school class), then you could change the analyis condition to flush the remaining sample(s) off the column to start a new equilibration.

Image attached.

The issue you described is not a problem for proteomic analysis and your statistical tests will be valid provided you appropriately normalize the data. Most current proteomic search tools (e.g., MaxQuant, Fragpipe, ProteomeDiscoverer) will correct for mass and retention time drift. Of course, it is always best practice to ensure your instrument is calibrated before running your samples. Once you have protein-level data output from your search software, there are several statistical tools for controlling intensity (abundance) normalization. One of the more common methods is to perform Tukey's median polish. After you have performed some type of statistical test between your groups, remember to correct for multiple hypothesis testing using Benjamini-Hochberg or Bonferroni procedure. This will ensure you have adequately controlled your false-discovery rate (FDR).

Your solvents have essentially zero retention time, as Dr. Umpierrez points out. You will not separate them; if you could then your mobile phase would consist of only acetonitrile. Impurities in your solvents are being continuously fed into your column so they, also, have essentially zero retention time. Typically they cause interferences in your detector, which you didn't bother to specify. I think you need to study basic chromatography before you attempt your analysis since your question indicates a very poor understanding of how HPLC works.

thank you Hans David

you can refer some papers

Thank you

Yes, I agree with W.J. Colonna, try adding the standard into your sample and see which peak increases the peak area.

You must use a more sophisticated instrument to differentiate between compounds that give similar fragments after collision in the MS.

A single quad MS will not differentiate between two different compounds if they fragment similarly. For example, in terpenes analysis, most of the terpenes will share common fragments. When you try to identify the peaks using the NIST library, you may find that three or more peaks suggestively belong to the same terpenoid. This doesn't make sense for un-experienced people. But with experience, you'll understand that the NIST library or any other library works by matching fragmentation pattern to those already in the library and then gives you a probability that this peak is compound A or B. Let me give you a simple example: Assume you have three compounds in plant leaf: Limonene, beta-pinene, and alpha-pinene. If all of these compounds give C2H2, C2H4, and C2H3OH fragments when they are collided with the collision gas, then actually the detector is collecting similar fragments for three different compounds at three different retention times. The second thing the library search does is to match the intensity of these fragments to its database. This means if both alpha and beta pinene have a similar intensity for C2H2, C2H4, and C2H3OH, then there is no way that library search can tell you for sure which peak is alpha and which peak is beta.

To solve this problem, you have two options: Easy and Hard. The easy one is to obtain pure standard materials for the expected compounds in your actual sample, and inject these standards individually into the GC-MS to identify retention times before injecting the real sample. The hard one is to replace the single quad MS by a triple quad MS (MSMS) so that the instrument can filter out unwanted ions and focus only on the desired ions.

This study that should be useful.

good luck

Thank you very much for that advice that information is really helpful.

Variable RT can be observed if the column has been stored prior to use, if not properly conditioned. In reverse phase chromatography that usually involves fully hydrating the stationary phase. Once conditioned, RT should be consistent for each compound in the separation unless there is some other problem with the column.

I can remember that RI (retention index) or KI (Kovats index) values are not absolute but comparative to reference/standard compounds.

They are also dependent on the type of column used. certainly, I therefore need standards. GC-MS has suggested my hits from the internal libraries (not exhaustive) which I need to be confirmed by comparison with authentic samples, RI or KI.

Please help.

Hi Daria, doing a quick literature search will help you to get a basic answer to your question. As with any search, the keywords used are important. In your case, you might first use "Total Rewards." I attached an article that I hope will help to get you started. You can also take a look at the sources used in the article.

It is so difficult to live with stress, how can we work with It? We should manage our stress ,then life will looks better and people too! ,then you can work better.Regards

Maybe you can try using a size exclusion method, searching a porous column that suits you depending of the mobile phase you are using

I don't have a citation for you, but customer retention is the result of the feeling of a relationship between the consumer and the business (or the product). Good customer service increases the positive feeling of the relationship. Bad customer service reduces positive feelings.

Thank you for your answer Tabrez Shaikh

Dear Sebastian,

interesting question! But I think it's not a question that can be answered in any straightforward way. Heat moves through the Earth's atmosphere in very diverse ways and on an array of different spatio-temporal scales. Please note that a certain amount of the energy released in what you referr to as an "exceptional heat event" would be absorbed by water bodies such as the ocean, the soil and other Earth system components. Please also consider for your calculations the fact that extensive wild fires may sometimes result - with some time-lag - in (regional-scale) scale cooling through ash particles being released into the atmosphere ("nuclear winter effect"). So this is all very complex. Heat transport through the atmosphere is governered by highly complex thermodynamic equations.

Where are you aiming to get at with such a calculation? Just interested :-)

Best,

Julius

It is significant for companies to employ customer retention strategies in order to retain talented manpower

Dear Harsha,

this is certainly a very interesting technical question, but unfortunately I'm not an expert in this field of research as we work in synthetic inorganic chemistry. However, you can easily find some helpful information right here on RG. For example, please have a look at the answers given to the following closely related question which has been posted earlier on RG:

(5 answers)

There are also some relevant literature references available, which have been posted by the authors as public full exts on RG:

and

I hope this helps. Good luck with your work!

As per my experimental experience, it is surely possible. The main concern is the effect of the matrix. Another point to be noted is that the first peak is coming out very early and it will be highly affected by the matrix in your case plasma, hence unsuitable for developing the bioanalytical protocol. As such a normal RHPLC protocol will not work, u also need to add an internal standard to maintain the integrity of the data. Furthermore, plasma peaks will not be stable so I don't think they will remain in the same place throughout the analysis.

Mrs/Miss Saxena,

By means of chromatography, there is unable to be determined tautomers and different protonated forms; if any. This can be done only by means of mass spectrometry; furthermore, exactly in terms of both quantitative and 3D molecular structural analyses.

Please, consider the following work. It deals, namely, with this issue:

[https://www.sciencedirect.com/science/article/abs/pii/S002228602200374X]

The shown method is applicable to a set of different MS ionization and fragmentation MS methods. Please, consider the reference section, therein.