Historically, Friday the 13th has become a day to be wary.
Click Here to view some history of Friday the 13th.
Or, for those more inclined, a limerick below courtesy of Brian Bilston Twitter Posting/London Telegraph
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This procedure is outlined for snack foods that may or may not be ground in the lab for analysis or powder and bulk solid or similar applications. Double-Blind Samples are recommended for calibration and validation. This allows the sensitivity or span (linear regression slope) to be accurately determined in the laboratory to speed up the calibration of on-line transmitter when it’s difficult to create a range of process moisture samples on-line.
Step 1: Collect sufficient product for about four or five samples of 200 grams each.
Step 2: Measure 100 grams +/- 2 grams and place into a sealed Bag or container.
This will be sample 1.
Step 3: Measure 100 grams and spray about 2 grams of water on the sample. Mix
the sample and place into a sealed bag or container. This will be sample 2.
Step 4: Measure 100 grams and spray about 4 grams of water on the sample. Mix
the sample and place into a sealed bag or container. This will be sample 3.
Step 5: Measure 100 grams and place in an oven with a temperature of 100 degrees C.
Leave this sample in the oven for 10 minutes*. Remove from the oven and
Place into a sealed Bag or Container. This will be Sample 4.
Note: If a fifth sample is used repeat Step 5, but keep in oven for 20 minutes*.
Step 6: Leave these samples in the Sealed Bag or Container for at least four hours to equlibrate.
Step 7: Take Sample 1 and place under the MCT. Record the moisture measurement.
Step 8: Do the Normal Lab analysis for this sample. A Confection Oven or
Vacuum Oven is recommended.
Step 9: Repeat Steps 7 and 8 for the remaining samples. When all the samples are
Analyzed, we can begin the MCT Calibration Routine. This can either be performed
via the MCT Operator Interface panel or by using the PSC Viewer Suite software. Entering the Lab vs. MCT Near Infrared Transmitter Data allows for a linear regression to be performed and the new Span/Sensitivity (Linear Regression Slope) and Zero/Offset (Linear Regression Y- Intercept) to automatically be generated for correct calibration.
Step 10: Confirm calibration by collecting sample on-line within target set point values and only make a zero or offset adjustment based on double-blind lab sample. Congratulations!
* Theseare variable.
Some products may need more or less water. Some products may take more or less time. Please contact PSC to discuss any questions or to request our assistance.
Samples should be collected and immediately taken to the laboratory or packaged for shipment to an outside lab in a sealed moisture barrier container or bag. If sending samples to an outside lab an additional moisture barrier tape should be applied around container lid. If samples are delivered to an in-house lab the procedure must outline for lab personnel the time to grind or process sample prior to measurement.
Calibration samples should be done individually meaning that sample one is ground, weighed, placed in oven for specified time interval at specified temperature for that product and weighed again for moisture determination. At that point the next sample is processed. Grinding all samples initially introduces an opportunity for increased variation while they await analysis unless all samples can be placed in the same oven immediately.
Consistency is the key to this process. If the first shift collects samples and the lab analyzes these samples when received, results are good. If another shift or operator collects the samples in a different manner or lets them sit for a while before bringing to the lab, or the lab lets samples accumulate before processing, variations can occur. Consistency is important for successful calibration.
Alternatively, samples can be created in the lab and allowed to equilibrate. These samples can be used for calibration. A final double- blind target set point sample should be analyzed and averaged to determine any offset (zero) adjustment on-line.
Other parameters such as fat and oil are subject to stratification and a well-mixed double-blind sample analysis is even more important for these constituents during calibration.
Process Sensors is seeking to expand representation and service of our product line in some parts of Central and South America. Our areas of interest are outlined below. Process Sensors offers a complete line of Near IR and RF gauges for industrial manufacturers who need to measure moisture, oil/fat, additives, Cross Direction Web Profiles and other systems. Systems are for process, at-line and lab applications.
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Photometers are both well suited and established for the measurement of moisture, oil/fat and other easy to identify applications. Photometers typically use targeted measure wavelengths where the parameter absorbs such as 1.94 microns for water and 1.72 microns for oil. The Photometer then compares the response with non-absorbing wavelengths. Sugar sprays can be measured based on the water carrier and flavorings based on the oil. Photometers are typically the best choice for these types of applications.
Spectrophotometers measure the full spectrum and then use slices of that spectrum, not the whole spectrum, to generate factors via chemometrics or mathematical modeling such as PCR, PLS, Neural Networks and other treatments. When the parameters being measured have overlapping absorption bonds such as different types of alcohols or saturated and unsaturated fats, they can discriminate between the constituents. Also, for more difficult applications such as protein, salt, sugar, ash etc. spectrophotometers have advantages over photometers.
Calibrations for Photometers typically need 3 to 7 samples throughout the range of interest. Calibrations for Spectrophotometers typically need 10 to 15 samples per modeling factor and can require as many as 200 or more samples to calibrate.
Photometers are significantly less expensive, easier to calibrate and easier for unskilled workers to operate. If a Photometer meets your measurement needs, it’s a better choice for on-line, at-line and lab measurements.
A Visit from St. Nicholas
‘Twas the night before Christmas, when all through the house
Not a creature was stirring, not even a mouse;
The stockings were hung by the chimney with care,
In hopes that St. Nicholas soon would be there;
The children were nestled all snug in their beds;
While visions of sugar-plums danced in their heads;
And mamma in her ‘kerchief, and I in my cap,
Had just settled our brains for a long winter’s nap,
When out on the lawn there arose such a clatter,
I sprang from my bed to see what was the matter.
Away to the window I flew like a flash,
Tore open the shutters and threw up the sash.
The moon on the breast of the new-fallen snow,
Gave a lustre of midday to objects below,
When what to my wondering eyes did appear,
But a miniature sleigh and eight tiny rein-deer,
With a little old driver so lively and quick,
I knew in a moment he must be St. Nick.
More rapid than eagles his coursers they came,
And he whistled, and shouted, and called them by name:
“Now, Dasher! now, Dancer! now Prancer and Vixen!
On, Comet! on, Cupid! on, Donner and Blitzen!
To the top of the porch! to the top of the wall!
Now dash away! dash away! dash away all!”
As leaves that before the wild hurricane fly,
When they meet with an obstacle, mount to the sky;
So up to the housetop the coursers they flew
With the sleigh full of toys, and St. Nicholas too—
And then, in a twinkling, I heard on the roof
The prancing and pawing of each little hoof.
As I drew in my head, and was turning around,
Down the chimney St. Nicholas came with a bound.
He was dressed all in fur, from his head to his foot,
And his clothes were all tarnished with ashes and soot;
A bundle of toys he had flung on his back,
And he looked like a pedler just opening his pack.
His eyes—how they twinkled! his dimples, how merry!
His cheeks were like roses, his nose like a cherry!
His droll little mouth was drawn up like a bow,
And the beard on his chin was as white as the snow;
The stump of a pipe he held tight in his teeth,
And the smoke, it encircled his head like a wreath;
He had a broad face and a little round belly
That shook when he laughed, like a bowl full of jelly.
He was chubby and plump, a right jolly old elf,
And I laughed when I saw him, in spite of myself;
A wink of his eye and a twist of his head
Soon gave me to know I had nothing to dread;
He spoke not a word, but went straight to his work,
And filled all the stockings; then turned with a jerk,
And laying his finger aside of his nose,
And giving a nod, up the chimney he rose;
He sprang to his sleigh, to his team gave a whistle,
And away they all flew like the down of a thistle.
But I heard him exclaim, ere he drove out of sight—
“Happy Christmas to all, and to all a good night!”
Some believe that this originates from the date that the Knights Templar were arrested and their assets seized under the orders of French King Phillip IV on Friday the 13th, 1307. The Knights Templar name was derived from their first headquarters established in Jerusalem as Temple of Solomon in 1120 in the captured Al Aqsa Mosque on the Temple Mount which was allegedly built upon the ruins of Solomon’s original temple.
The Knights Templar were formed to protect Christian Pilgrims on their journey to Jerusalem and started with nine knights including Godfrey de Saint-Omer and André de Montbard. Their emblem of two Knights riding a single horse represented their poverty compared to other rival Knightly Orders such as Hospitaller and Teutonic . They lived on donations from Christian nobleman and Kings and were granted special privileges by the Church. Quickly their Order grew in size and assets. The likely high point of their military crusades was the defeat of Saladin’s army of 26,000 at the Battle of Montgisard with a few thousand soldiers led by 500 Templar Knights with their fierce attacks in full armor mounted on horses in 1177.
Over the years, the Knight Templars influence grew far away from the battlefield with administration, castles and estates in France and England. They developed one of the first banking systems so that travelers could make a deposit at the local Templar and receive a coded letter that when delivered to another Templar site allowed them to receive funds less a donation. This allowed travelers to avoid being robbed of gold or other riches by bandits when traveling.
As leadership changed, so did the Knights fortune. The Knights Templar rode across a desert in full armor with no rest to reach the Battle of the Horns of Hattin in 1187 where they were defeated soundly by Saladin when Muslim forces recaptured Jerusalem. Their military influence waned to non-existent as their financial position rapidly grew. While the Knights took an oath of poverty, the wealth the Order controlled was vast.
King Phillip the IV persuaded the new Pope Clement who had moved the Catholic Curia to Avignon France and under Phillip’s influence to investigate alleged crimes of the order so as to avoid paying the huge debt he owed the Knights Templar from financing his war with England. The Knights were accused of Satanic and Pagan like rituals and Heresy.
And so, on the morning of Friday the 13th, 1307 began the destruction of the order with the arrests and torture of the Knights culminating with Grand Master Jaques de Molay and Geoffroi de Charney, Preceptor of Normandy, being burnt at the stake in Paris on March 18, 1314 after recanting their earlier confessions. Jaques de Molay allegedly screamed through the flames that “God knows who is wrong and has sinned and a calamity will occur to those who condemned us to death”. Pope Clement died within a month and King Phillip died of a hunting accident within a year.
The Great Fortune of the Knights Templar was never found and legends abound with most featuring escapes with Treasure by the surviving Knights to England, Scotland, and North America.
Jun Funashashi is a solution oriented engineer with strong experience in sales, engineering, manufacturing and customer service. Jun has 20+ years of experience in designing, supporting and selling special solutions for process control and industrial automation applications. He is also fluent in English and Japanese. Jun will be working out of the Chicago area on national and international projects. Process Sensors welcomes Jun to better serve you, our customers.