Citrus sinensis - Science topic

To extract compounds from fresh orange peel, you can use a variety of techniques that will preserve the bioactive components while preventing degradation. Here are some commonly used methods for extracting from fresh orange peel:

Description:Cold pressing is a common technique used for extracting essential oils and juice from citrus peels. In this method, the fresh peel is mechanically pressed or squeezed to extract the volatile compounds (mainly essential oils) and juice.

Description:Solvent extraction involves using a solvent (such as ethanol, hexane, or dichloromethane) to dissolve and extract essential oils and other lipophilic compounds from the fresh peel.

Description:Steam distillation is a traditional method for extracting essential oils. In this process, steam is used to separate volatile compounds from the fresh peel.

Description:Soxhlet extraction uses a continuous extraction method where the solvent is repeatedly cycled over the fresh peel to extract components over time.

Description:Ultrasonic extraction utilizes high-frequency sound waves to create cavitation bubbles in the solvent, which increases the mass transfer of compounds from the orange peel to the solvent.

Description:Maceration is a simple method where the fresh peel is soaked in a solvent at room temperature, and the compounds are extracted by diffusion over time.

Each of these methods has its advantages, depending on the compounds you're looking to extract and the specific application.

The blue curve shows a smoother, more stable transition in the force, indicating better system stability with a lower perturbation. The small plateau or microstate you notice is not uncommon and may not be an issue, but it can be further investigated by refining the force constant or simulation parameters.

The orange curve shows a sharper peak and potentially more disturbance due to the higher force constant and velocity. While it can still be valid, the smoother blue curve is typically preferred to avoid introducing large perturbations.

All of which can we easily done at mdsim360.com, a new platform that lets you run MD simulations entirely online without local installation.

Although some studies do not agree with the use of citrus fruits due to acidity, my own experience has proven the opposite.

The high fluorescence at low temperatures for your protein could be due to:

1. Increased protein stability

2. Reduced protein denaturation

3. Enhanced fluorophore binding

4. Decreased quenching

5. Changes in protein conformation

Temperature-dependent fluorescence:

At lower temperatures:

- Protein movements slow down, reducing quenching.

- Fluorophores may bind more tightly, increasing fluorescence.

- Protein structure becomes more rigid, enhancing fluorescence.

Possible explanations:

1. Hydrophobic interactions: Low temperatures strengthen hydrophobic interactions, stabilizing protein structur

e.

2. Hydrogen bonding: Low temperatures enhance hydrogen bonding, stabilizing protein-fuorophore complex.

3. Reduced protein aggregation: Low temperatures minimize aggregation, increasing fluorescent protein population.

Consider:

1. Protein purification and quality

2. Buffer composition and pH

3. Fluorophore properties and concentration

4. Instrument settings and calibration

To confirm:

1. Perform temperature-dependent fluorescence titration.

2. Measure protein stability using circular dichroism (CD) or differential scanning fluorimetry (DSF).

3. Test protein-fuorophore interaction using fluorescence lifetime measurements.

Oemniyah Mohammed Ashim

Based on the information provided, the scale can be treated as an ordinal scale for color (Yellowness) but not an interval or linear one for color. Because color is a perception, the degree of "yellowness" differs from mere pigmentation. In addition, there is no consensus definition for what is called "yellowness." Mere pigmentation is physical and linear.

No it is just some leftover debris on your plate. Might be a manufacturing error but won't really impact your culture. Try to adjust the soft knob to focus on your cells, it'll disappear because it's in a different layer than the cells. If your cells are suddenly misbehaving, report this issue to your supplier.

I don't doubt the UV light source. I think that the UV light might be absorbed by the glass of the beaker. So, no UV light reaches the inside and the degradation cannot take. But I don't know.

In summary, the ability of methyl orange to absorb visible light, facilitate electron transfer, and provide stable, cost-effective sensitization makes it the preferred choice in many photodegradation studies compared to other dyes that may lack these beneficial properties.

Bree Barand do you also include the formalin fixation and then 3 washes in 100% EtOH before staining?

Extracting formaldehyde from a fruit like a banana or orange would be challenging because formaldehyde is not a natural component of fruits. Formaldehyde is primarily used as a preservative in some foods but not typically found naturally occurring in fruits. However, if you're interested in extracting formaldehyde for some specific purpose, such as analytical testing or research, you would likely need to employ chemical methods rather than extraction from fruits.

One possible method to extract formaldehyde from a food sample involves acid hydrolysis followed by derivatization. Here's a simplified outline of the process:

1. Sample Preparation: Start by preparing your fruit sample. Crush or blend the fruit to a homogenous mixture.

2. Acid Hydrolysis: Add an acidic solution to the fruit sample. This will hydrolyze any formaldehyde-bound compounds, releasing formaldehyde into solution.

3. Derivatization: Formaldehyde is highly reactive and can form adducts with various compounds. Derivatization involves reacting formaldehyde with a suitable reagent to form a stable derivative that can be more easily analyzed or detected.

4. Extraction: Depending on the specific method and derivatization used, you may need to extract the formaldehyde derivative from the solution to separate it from other components.

5. Analysis: Finally, analyze the extracted formaldehyde derivative using analytical techniques such as gas chromatography-mass spectrometry (GC-MS) or high-performance liquid chromatography (HPLC) to quantify the amount of formaldehyde present.

Keep in mind that handling formaldehyde and performing chemical extractions requires proper safety precautions and expertise in laboratory techniques. Additionally, if you're considering this for any practical application, it's crucial to ensure compliance with regulations regarding the use and handling of formaldehyde.

The DAPI excitation peak is at 359 nm and the emission peak is at 457 nm. The Calcium Orange excitation peak is at 549 nm and the emission peak is at 574 nm. (There needs to be esterase activity present to cleave the AM ester off the calcium orange.) Therefore, the fluorescence ranges can be separated by flow cytometry and fluorescence microscopy optical filters, allowing the two dyes to be used together.

All enzymes that work on DNA have Mg2+ as a cofactor. So, I think the EDTA you have in your buffer will already do the job, as it complexes the Mg2+. Concerning proteins bound to DNA, an alternative to phenol extraction is to use proteinase K for the deproteinization of the samples.

Hello Friends 🎄

Season's greetings🎄

I recomend my abstract in the bilmescongress🍄

Effects of gamma radiation and electron beam on samples of the Peanut Candies contaminated with Aspergillus flavus🍞

Gisele Ferreira de Souza1,🇧🇷

Laith Khalil Tawfeeq Al-Ani2m

🇧🇷

1 University of Sao Paulo, Brazil

2 School of Biology Science, Universiti Sains Malaysia, 11800 Minden, Pulau Pinang, Malaysia;

* Corresponding Author (Gisele Ferreira de Souza)🍠

Abstract🍩

Peanuts is known usage in making foods and generation of oil in Brazil like peanut candies and potential contaminated with several mycotoxigenic fungi as Aspergillus flavus. Therefore, it is possible A. flavus secreting some mycotoxins into contamination peanuts.🍬

This study is aimed to determine effects of gamma radiation and electron beam in reduction peanut candies contaminated with A, flavus. The samples of peanut candies were included two types of peanut candy, (A) Diet Peanut Candies, (B) Organic Peanuts Candies that divided treatments divided into two groups First: contaminated groups with A. flavus, and Second: control without contaminated which receive radiation of 0, 5 and 10 kGy dosage of electron beam EB and gamma radiation GR. Some samples of No inoculation were illuminated with a similar dosage to evaluate the sensors. 🍕

The results indicated that 0.80 of the samples had an average water capacity. Illumination or irradiation of gamma radiation and electron beam at a dosage of 5 and 10 kGy were able to eliminate the A. flavus in the samples of Brazil peanuts. Analyzes of Aflatoxin indicated that electron beam doses of 5 and 10 kGy lowers aflatoxins levels by 53.32 and 65.66% correspondingly. Moreover this same dosage of gamma radiation lowered the levels of toxins by 70.61 and 84.15% respectively as compared to the control groups. The irradiation energy could affect A. flavus without change in characterize tastes of peanut candy and potential reduction mycotoxins in this candy. 🍭

You may find the answer here

( )

However, a number of factors can affect the concentration of Methyl Orange dye in textile wastewater, including the type of dye used, the dyeing process, and wastewater treatment efficiency. There are generally a few milligrams per liter (mg/L) to several hundred milligrams per liter (mg/L) of dyes in textile wastewater.

@all The concentration of acridine orange for staining DNA in a comet assay can vary depending on the specific protocol and the sensitivity required for your experiment. However, a common concentration range for acridine orange staining in comet assays is typically between 1 and 10 μg/mL. Here are some considerations:

Remember to document the concentrations and conditions you use during optimization, and keep track of any changes made. If you are still facing issues with staining, it may be helpful to consult published protocols, reach out to colleagues with experience in comet assays, or consider contacting the manufacturer of the acridine orange for specific recommendations.

Additionally, consider assessing the overall health and integrity of your gill samples, as exposure to pesticides might affect the structural integrity of cells and impact the results of the comet assay.

Kouadri Mohamed El Amine indeed, it seems rust spores and Alnus is a tree growing on the riverbanks of the river where this orange scum layer developed! It seems this rust spore concentration on water is a rare phenomenon. Many thanks for the suggestion and potentially identification!

cheers,

Jeroen

Here is the SDS of methyl orange - I have no clue whether it has lambda max 418 nm but if you have a spectrophotometer (dual) then that does not matter

The peak of the absorption spectrum is at 361 nm, which is in the UV, but there is nonzero absorbance at wavelengths between 400 and 500 nm, which is in the visible. The spectrum is dominated absorbance by the shorter (violet) wavelengths, which gives a yellow color, with just enough of the blue wavelength absorbance to give it an orange color.

Sigma and Thermo-Fisher sell it. Certificates of analysis may be available at the vendor's web site once you have the lot number.

Dear Hakim Bout, melt extrusion defects are the consequences of many processing parameters, MWD is one of them, since diferent lengths chains have differents relaxation responses (times) while recalling at the exist of the dies. My Regards

How are you

Can you write the question in English?

Yes, I use it all the time. Works great for NIR scanning with a LiCor. LiCor sells a pre-made 4X loading solution.

No, methyl orange will decay at 300‒500 °C. It represents an azo dye: sodium 4-[(4-dimethylamino)phenylazo]benzenesulfonate, and the azo functional group would not survive heating at 300‒500 °C. Methyl orange can break down to mutagenic radicals at various conditions, so be careful when handling solutions of it.

Hi there,

As when you perform gel purification, the silica column purification process allows to remove the DNA "staining" molecules...

Airbubbles could be also responsible for such images. Another reason: If you are proceeding your immuno on slides, it could be the case that somtimes the antibody solution gets behind the sections. This explaines the more intensiv staining result in the border area. I recommand the free floating method when you are working with fixed sections of thickness more then 20µm. This technique could help to prevent such fenomena.

Shoyab Ansari I found your email thread with our Tech Support. I am replying to it with some additional thoughts. Please feel free to reply back if you have any questions.

First of all it might be due to other types of contamination (e.g. fungi) or expired/contaminated materials. If you are using RPMI-1640 powder make sure you add bicarbonate and keep the solution in the dark. Double check the protocol provided by the manufacturer. If none of these works, here is a reliable protocol for MG63 cell culture you can use instead. Good luck.

Thanks, I will try reducing the Sypro. Do you work with sypro in the dark? I keep the solution dark but then set up the plate with light, I am wondering if plate set up needs to be done in the dark?

I am seeing this phenomena in a non-quartz vial.

Thank you for the reference!

Thanks, please prepare very dilute solution and check absorbance, which should not more than 1

Methyl orange can form a Zwitterion ion (both positive and negatively charged groups on the same molecule). It also is a flat planar molecule with two hydrophobic aromatic rings which would like to remain on the water's surface, while the charged regions, would like to be solvated by the water, however these charge regions of the methyl orange molecule can form hydrogen bond with each other producing an interlinked elastic film on the waters surface and increasing the surface tension.

Hi, we had somewhat the same issue and in our hands this was not contamination. ExpiCHO cells have always the tendency to clump a bit and we noticed that when we started production from a culture with too many clumps, the end result looked somewhat what you have there. We 'fixed' the problem by filtering our culture every few weeks. Hope this helps, Lennart.

You can follow two strategies; one is to design a new pair of primers with desired restriction sites on the 5’ end, then run a PCR to amplify the gene of interest, and thereafter the cloning. The second strategy can be reached by making the sticky ends blunt. To remove the 3' overhangs or fill up the 5' overhangs you can use the Klenow fragment. Therefore, you can clone the blunt-ended fragment in any site with blunt ends. Remember to screen colonies to find that the gene has been cloned in the correct direction (5' to 3').

Hello , your cells may be infected with virus, fungus, mycoplasma. Or your cells are old. Did you check with an invert microscope that the cytoplasm of your cell was not vacuoled or that its membrane was not wrinkled and that the nucleus membrane was not granular? Because if these things happened to your cell. Your culture medium turns orange quickly and your cells die sooner .

The colors are representing p-values (statistical significance). Only red and black means that your results are statistically significant. Orange and yellow means that your results are not significant. I am not sure about ASAP but I would expect that significance here refers to the partitioning.

@Ishak, that is a challenge for tree crops modelling. However, simulation of water use efficiency model can provide reliable yield estimate. I have attached below a paper that I found really useful in this regard.

What is your dependant variable?

Interesting question

Also check please the following useful RG link:

Hi J. Ramirez-Franco , here is an image, the staining is not very strong..

You can substitute BHA as an antioxidant; it eliminates the formation of colored stilbene-like products. BHA is cheap and easier to get than more hindered phenols.

Also, if I didn't mention it before, you should keep your alkaline glycol solutions in plastic containers, not glass. Glass gradually releases iron, which contributes to discoloration as a catalyst for oxidation. You didn't mention the type of container in your reply, and your picture shows glass containers.

If you can spend some $$ then try an idea inspired by the new "non-yellowing" antioxidants for polyurethane foams such as "Omnistab AN 1135" : https://www.partinchem.com/products/omnistab-an-1135/

These were demonstrated to stop a similar yellowing problem in polyurethane foam that was formerly thought unsolvable. The principle is to use a much more hindered aminophenol than BHT. 2,4,6-tri-tert-butyl phenol would be the closest commercially available reagent like this.

Phosphites are another antioxidant used to prevent discoloration. Phosphites are slower to react with oxygen and peroxides, but are complete in the sense that they can lower oxygen levels to below detectable limits. A similar phosphite-based antioxidant from the same source above is omnistab-an-6136. Both of these "omnistab" products have side-chains that consist of branched, high-molecular weight alkanes. You don't need these necessarily, as they are intended to act like plasticizers in the yellowing polymers. Instead, you may want to test something commercially available in small amounts like tri-isopropyl phosphite or di-tert-butylphosphite at a concentration of 0.5% to see if that works better than BHT. If it does, lower the phosphite concentration until you reach the minimum amount of time for which you want the solution to remain colorless. Phosphites scavenge oxygen, becoming phosphates in the process; hindered phosphates and similar hindered phosphite esters are generally non-nucleophilic and being hindered, should have little effect on reactions. Hindered tri-alkyl phosphites are also higher-boiling than ethanol, but can be distilled off at reduced pressure. Some are checked-for as known impurities in pharmaceutical drugs.

Depending on your chemistry, it may be advantageous to know that tri-aryl phosphines also scavenge oxygen; triphenyl phosphine is a commercially-available example. Triphenyl phosphine reacts slowly with air at ambient temperature, so it must be handled quickly in air. Both triphenylphosphine and triphenylphospine oxide can be difficult to remove from reaction products. This makes them disadvantageous with respect to phosphites, which generally can be distilled under reduced pressure or extracted by water washes during workup of a reaction. Triphenylphosphine immobilized on resins might also help scavenge oxygen from your alkaline ethanol solutions, and the resin beads should be easy to remove when exhausted.

I would not recommend tri-alkyl phosphines as antioxidants as these are typically too reactive toward oxygen; they can be pyrophoric (burst into flame in contact with air), even in dilute solutions. They also participate in reactions with ketones and aldehydes to make alkenes (Wittig reaction).

It's little comfort but the best minds in industry and academia also find this problem vexing.

That's all I can contribute on the subject. Hopefully another contributor will have better ideas or more experience.

Sorry for asking: does IHC mean that you have a brightfield RGB image with one channel or a multichannel image? If the latter is true, I agree with Molly Brady. But for the other case you would need to do color deconvolution instead of splitting the channels.

Fiji has a number of predefined color deconvolution vectors (Image --> Color --> Color deconvolution). Since I don't know your staining, I don't know if there is one working for you.

Alternatively there is the plugin Color Deconvolution 2, which offers some extra features: https://academic.oup.com/bioinformatics/article/37/10/1485/5913390?guestAccessKey=148a8a4b-24f8-4b42-8742-e985535c9410

And there are of course also other programms, such as Qupath, where you manually annotate cells of interest for automated analysis of the whole sample: https://qupath.readthedocs.io/en/stable/docs/tutorials/cell_detection.html

Totally agreed!

Hello Danna Sofia Camelo ,

Could the water be contaminated? Have you tried inoculating the plates with just the same water, and other plates without adding anything but pretending to inoculate them (taking off the lid, pipetting air, etc. - all the physical steps of inoculating), i.e., performing a negative control on the water?

Regards,

Tom Cuff

Hmmm. About the smaller sample size and the lower R-squared. I said "The smaller sample size made the regression coefficient standard errors larger, which would make a given sigma smaller in comparison." But I think I'm mistaken in thinking that makes R-squared smaller, but instead, just more volatile. (A quick check on the internet and remembering back a little indicates I was wrong about R-squared.)

Dear Marco Caruso ,

I would like to thought about the solution with you. That is what I said here is just a proposal hoping it will be beneficial to you.

You have to look at the independent parameters of the two error functions.

If the independent parameters of every one is are different for each of them, then you can optimize every error independent from the other.

If there is mixing of the independent parameters and dependent parameters then you can try the minimization process by independent parameters for each one independently till you get an acceptable error.

If you could not reach the acceptable error, then you can study the minimization of the two together by the adjusting the common parameters.

This may be one possible scheme for solving the problem.

I think there are mathematical tools for multi objective minimization or maximization. Please follow the link:

Best wishes

Dear Lee,

If the number of partitions, which are needed, is too much (as the number of studs are). That would be time consuming to do it for each stud, also the corrections in mesh or partition (if needed) become difficult.

In such cases that would be probably better to make a script (python code) - get a "Macro" from partition command in Abaqus, then make it parametric and run the code for partitioning, in such way edits become much more easier.

Depends on the place you want to partition, you need just to change sum values in your macro instead of do the partition command again and again. Generally for repetitive commands, it's better to use programming rather than UI(user interface). ( File - Macro Manager - Create Macro)

Hope it helps

Yuri Mirgorod thank you sir for responding

For applying the same, you need 12 degree of freedom. You have 3 treatments. 5 subplots can be treated as replication. Then your df is only 8. If you have 4 treatments, it would be good.

Expecting comments from the statisticians.

Also check https://www.mdpi.com/2075-4450/11/8/474/htm

The adsorbent may itself contribute to the absorbance. To correct for this, you should prepare two identical samples differing only in that one of them had no methyl orange in it initially. Then subtract the absorbance of this "blank" from the absorbance of the sample that contained methyl orange.

In addition, you should include in the sample solutions a strong pH buffer for the desired pH to prevent a change in the absorbance spectrum of methyl orange due to a change in pH.

Dear Ahmed,

The treated sample FTIR peak and control sample FTIT seem to be the same and the only differences between them is the amount of transmitance%. In this situation there would be no change in chemical structure of the main sample or if there is, it might be negligible. To be sure about it, it is necessary to make a comparision between the ratio of all FTIR peaks of control and treated samples. For example, the ratio of %T of control sample to the treated sample at 2915, 2848, 1467, 876, and 717 must be calculated. If the difference between all of them is meaningful, so it is acceptable to consider change in chemical structure during treating. Otherwise, it is not possible to consider that its chemical structure was changed.

Dear Basmaa S. Sheet Albakry ,

Choosing the proper method to determine color of fruit juices depends on how you define/express color and what you want/need this value for?

If you are interested in color, as a general concept/value, you need a color meter which reads out color data e.g. by using the Hunter L-a-b- color-scale. This is a three number code that specifies your color. No need to buy an instrument, this article instructs how to do this with a smart phone:

Big advantage of 'color' measurement is that it uses the complete sample so including pulp and other solids which may contribute to color!

If you are interested in dissolved species that give the color, which are mostly anthocyanins, you need to register spectral data using a UV-VIS spectrometer. Downside is you need to remove solids as they generate a lot of background signal. I worked with grape juice and first spun down the juice in a centrifuge at 5000 rpm, next I used the clear liquid to further dilute in buffer (anthocyanins spectral data changes with pH) and record a spectrum from 900 to 300 nm. I recommend to read: which is the most comprehensive article on anthocyanins characterization.

Hoping this helps you further, kind regards, Leo

Also check https://core.ac.uk/download/pdf/234684199.pdf

Hi Carolina,

I have not done a lot of XRF work on samples with large porphyroblasts or phenocrysts so take what I say below with a grain of salt (or crushed garnet hornblende gneiss).

It might help to prepare several aliquots, maybe 7 or 8, from what you believe to be representative subsamples. Then, take equal portions of each and add to an additional aliquot which you you will ultimately fuse. If you want to be extra careful, you can then run each of the 7 or 8 aliquots to see what the range is and how it compares to your "mixed" aliquot sample. While time consuming, I think it is likely that doing this will give you a "representative" sample of the chemistry of the rock.

Ryan

Hi Luciana

The determination of nutrient concentration as described by Mattos Jr. (2000),

You can check this reference:

This image explains it completely. Thank you so much.

Philip G Penketh

Maybe a Chloride Ion Selective Electrode?

Or ionic chromatography?

Dear Mahsa Amiri many thanks indeed for your very interesting technical question. Actually, we have been working in the area of lanthanide and organolanthanide chemistry for more than 30 years, and we have already published a number of papers involving tetravalent cerium compound. The reference by Bill Evans of 1989 which you provided with your original question is quite familiar to me. The problem with the chemistry of tetravalent cerium alkoxide derivatives is that it looks simple but in practice it is not. We even used the compound (^tBuO)₃Ce(NO₃)(THF)₂ many years ago as starting material. I would say that the tetra-tert-butoxide complex Ce(O^tBu)₄(THF)₂ is perhaps easier accessible than the mixed-ligand nitrate species. However, in all cases one should take care of a few precautions:

1. It is very important to exactly use the given amounts of starting materials.

2. The quality of the precursor NaO^tBu is decisive for the outcome of these reactions.

Thus the question is if you used commercially available NaO^tBu or ion it was freshly prepared from tert-butanol and NaH as described in the Evans paper? The problem with commercial samples of NaO^tBu is that they are often partially hydrolyzed, which can be the reason for the observed low yield. I suggest that you freshly prepare your NaO^tBu from tert-butanol and sodium hydride (or clean pieces of metallic sodium) and then evaporate the solution (which should be completely clear) to dryness. Then make sure that remaining tert-butanol is completely removed under vacuum. For even better results the product NaO^tBu can even be sublimed under high vacuum. With this highly pure NaO^tBu the synthesis should give much higher yields.

For some general overview of organometallic cerium(IV) chemistry please have a look at our review article entitled:

This article is freely available as pubic full text on RG.

Good luck with your research! 👍

Might be caused by some kind of transformation into an interval with an upper bound. Divide your training data and set values by two and see what happens.

Regards,

Joachim

Use separating funnel and confirm its purity with GCMS.

Hi Faiza,

To staining cells and observe by fluorescent microscope, we use Calcein AM/PI to distinguish live/dead cells. For cells in hydrogel, mix your dye with culture medium and staining by replace the medium.

i never used them before but there exist something call Ultrasonic Energy Meter , and i am seeing that maybe you can get one of this devices and introduce the tip in your beaker and measure the intensity of the ultrasound inside of it, here is a link of the equipment:

www.megasonics.com/ultrasonics.html

sugars can break down in an acidic environment, disaccharides can become mono, changing their sweetening power

Dear Dr. Ang,

Did you resolve it?... I am experiencing the same problem. My water only control is changing from a pink to an orange color.

Dear Alessandro,

The terms Machine learning, data mining and data science are used interchangeable but there is difference between these terms. Basically all the terms revolve around dealing with the rapidly using large amount of data. Data science derives understanding from structed and unstructured data. It is used for qualitative analysis. It consist of data visualizations, data mining, language processing etc. It is a wider area of research which makes use of many algorithms and operations to derive informative insights from both structured and unstructured information. Where as data mining analyzes data sets created from structed data to find the hidden correlations and patterns. It is subset of data science used to extract data and generate prediction models. Data Mining also incorporates data cleaning, pattern prediction, statistical analysis, data conversion, machine learning, and data visualization. Both play key roles in helping organizations recognize opportunities and arrive at worthwhile decisions/conclusions so that they can take easily decisions to grow the businesses. Additionally, the knowledge needed for procedures in both of these fields also varies. Hence, the analysis of the differences in their approach, tools used and steps applied. Data science tools include Python, Apache spark, SAS, Tableau, R, Tensor flow etc. Data mining tools used as weka, rapid Miner, KNime, Oracle Data Mining, Apache Mahout, Teradata, Orange. These tools are not only used to teach/research but also used by industries to do the analysis as per requirements.

Math Mystery wrote: "My question is how do I find out if a specific Color is sig or not since SPSS will always use one of the value as baseline and the results become a comparison of 'odds of value 2 vs odds of value 3 being a YES'. I will like to know if value2=Orange is significant in affecting the dependent variable result."

Orange vs what? If all you care about is orange vs not orange, then use a single indicator variable for orange colour (1 = orange, 0 = not orange) in place of your 3-level categorical predictor.

Another possibility is that you want all pair-wise comparisons of the colours. If so, you can get them by using GENLIN (rather than LOGISTIC REGRESSION) to estimate your model. Here is an example showing that you can get exactly the same model using GENLIN. It uses one of the sample data sets that comes with SPSS. You'll need to change the path on the GET FILE command to show where you have those datasets stored. To make it work for your data, replace Male with your dependent variable, Age with salary, and Race with your colour variable.

* --- start of syntax ---.

NEW FILE.

DATASET CLOSE ALL.

* Edit the path on the next line as needed.

GET FILE = "C:\SPSSdata\survey_sample.sav".

* Compute an indicator variable for Male Sex to use as the outcome.

COMPUTE Male = sex EQ 1.

FORMATS Male (F1).

FREQUENCIES race.

LOGISTIC REGRESSION VARIABLES Male

/METHOD=ENTER race age

/CONTRAST (race)=Indicator(1)

/PRINT=CI(95)

/CRITERIA=PIN(0.05) POUT(0.10) ITERATE(20) CUT(0.5).

* Generalized Linear Models.

GENLIN Male (REFERENCE=FIRST) BY race (ORDER=DESCENDING) WITH age

/MODEL race age INTERCEPT=YES

DISTRIBUTION=BINOMIAL LINK=LOGIT

/CRITERIA METHOD=FISHER(1) SCALE=1 COVB=MODEL MAXITERATIONS=100 MAXSTEPHALVING=5

PCONVERGE=1E-006(ABSOLUTE) SINGULAR=1E-012 ANALYSISTYPE=3(WALD) CILEVEL=95 CITYPE=WALD

LIKELIHOOD=FULL

/EMMEANS TABLES=race SCALE=TRANSFORMED COMPARE=race CONTRAST=PAIRWISE PADJUST=LSD

/MISSING CLASSMISSING=EXCLUDE

/PRINT CPS DESCRIPTIVES MODELINFO FIT SUMMARY SOLUTION.

* --- end of syntax ---.

HTH.

Application of orange peel waste in the production of solid biofuels and biosorbents

The dry biomass and the biofuel showed moderate levels of carbon (44–62%), high levels of oxygen (30–47%), lower levels of hydrogen (3–6%), nitrogen (1–2.6%), sulfur (0.4–0.8%) and ash with a maximum of 7.8%. The activation energy was calculated using Kissinger method, involving a 3 step process: volatilization of water, biomass degradation and volatilization of the degradation products. The calorific value obtained was 19.3 MJ/kg. The studies of metal biosorption based on the Langmuir model obtained the best possible data fits. The results obtained in this work indicated that the potential use of waste orange peel as a biosorbent and as a solid biofuel are feasible, this product could be used in industrial processes, favoring the world economy.

Yes, it is possible to change the variable data using ranks or there is a feature that you work with while you change the names to numbers, for example: A = 1, B = 2 and so on

Hi there sadhan

Try this site: https://ndb.nal.usda.gov/

search the product you wish and it will give you its composition.

good luck

isaac