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With his thermometer made of a thick glass tube, 1.5 to 2 inches in diameter, and filled with linseed oil, he measured the temperature of melting snow. This temperature became his first defined point on the temperature scale. So he has assigned it the number 0.

So now that he had calibrated his thermometer, he could start measuring temperatures, but only in the lower range because linseed oil reaches its boiling point at about 287C (depending on the purity). Secondly, the oil starts to decompose around its boiling point which would change its coefficient of expansion, making the thermometer useless.

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Newton recorded the time when the iron block started to cool and also the times at which the different alloys solidified. Finally, he also noted the time when the iron had cooled down so much that its temperature could be measured directly with the linseed oil thermometer. This means that it had to cool down to body temperature.

Because precise temperature measurements are important in the field of physics and the thermometers that were used for this purpose were usually not very accurate, he developed his own thermometer in 1731.

In fact, even today in some parts of the food industry, the Raumur scale is still used. For measuring the temperature of milk during cheese production in Switzerland and Italy for example, or for cooking sugar syrup for the production of meringue in some countries of Western Europe.

It might seem a little odd to choose the temperature of a random cellar as a fixed point, but at that time a lot of scientists believed that the temperature of places underground was constant. In particular, they were persuaded that this temperature corresponded to an internal mean temperature at which the sun had brought the earth since its creation. This is of course not true, as we have found out later.

But with spirit of wine as a thermometric liquid, there was a serious problem, as spirit of wine boils at a lower temperature than water. Spirit of wine thermometers simply could not stand the heat of boiling water.

Originally the scale had 2400 divisions, appropriate to the winter in Saint Petersburg. Each division corresponded to one hundred thousandths of the contraction of the mercury in the thermometer, with higher values at lower temperatures.

The reason why he chose an upside-down scale was that at that time the thermometer was mainly used to measure the outside temperature or body temperature, which both fell within a range between -20 and +40 modern degrees Celsius.

Especially biologists found it interesting to invert the scale. Since plants are at risk of dying at 0C because the water is frozen, the scientists found it more obvious to indicate temperatures below the freezing point of water with negative numbers and temperatures above with positive numbers.

While relative temperature scales, e.g. Fahrenheit or Celsius, are comparing the temperature of an object to a randomly chosen fixed point (like the freezing point of water), absolute temperature scales work differently. They indicate temperatures compared to absolute zero.

In this way, absolute temperature scales are not only indicating the temperature of an object but also provide information about the amount of kinetic energy of its atoms and molecules. The kinetic energy is zero at a temperature of zero Kelvin and has a higher value at higher temperatures.

In 1859 he developed his temperature scale. It was a thermodynamic scale just like the one Kelvin had developed, but the Rankine scale was based on degrees Fahrenheit instead of degrees Celsius, as was the case for Kelvin.

The Rankine temperature scale is only applied for scientific applications when formulas are expressed in Imperial Units. It can be used for calculations like radiation heat transfer, entropy change, the Carnot Heat Engine thermal efficiency, or the Ideal Gas Law.

The Rankine scale has been largely replaced by the Kelvin scale. Nowadays, I imagine it is hard to find any scientific work making use of the Rankine unit. But, if you want to dive into old scientific papers, knowledge of this temperature scale can come in handy.

A few countries maintained the imperial or the customary system and continued to measure temperature in degrees Fahrenheit. Today, these countries are the United States, Liberia, and Myanmar. Some other countries use both Fahrenheit and Celsius.

When Carnot and Stirling initially conceptualized heat engines, temperature unambiguously represented our everyday perception of cold and hot. However, as this energy scale is expanded to measure the strength of noise in general nonequilibrium heat baths, such as those consisting of bacteria or active particles, it takes on different definitions and connotations. This raises a fundamental question of whether and how thermodynamic conclusions beyond a unique definition of temperature would deviate from our conventional understanding. To address this inquiry, we investigate a colloidal Stirling engine governed by a large number of stochastic dynamical systems. Within experimentally accessible parameter values, we discover certain exceptional active engines that can outperform their passive counterpart, as notably claimed in a recent experiment involving a bacterial bath. Our analysis shows that such heightened performance can be attributed to either a restoring effect in noise or a significant dissipation kernel. The revealed influence of active baths on Stirling efficiency provides further insights into their impact on maximum power output, Carnot efficiency, and Curzon-Alhborn efficiency. The finding elucidates the origins of exceptional performance in stochastic heat engines, offers strategies for harvesting energies from active noises, and sheds light on the effects of nonequilibrium temperature in stochastic thermodynamics.

Rattlesnakes, copperheads, and other pit vipers have highly sensitive heat detectors known as pit organs, which are used to sense and strike at prey. However, it is not currently known how temperature change triggers cellular and molecular events that activate neurons supplying the pit organ. We dissociated and cultured neurons from the trigeminal ganglia (TG) innervating the pit organs of the Western Diamondback rattlesnake (Crotalus atrox) and the copperhead (Agkistrodon contortix) to investigate electrophysiological responses to thermal stimuli. Whole cell voltage-clamp recordings indicated that 75% of the TG neurons from C. atrox and 74% of the TG neurons from A. contortix showed a unique temperature-activated inward current (IDeltaT). We also found an IDeltaT-like current in 15% of TG neurons from the common garter snake, a species that does not have a specialized heat-sensing organ. A steep rise in the current-temperature relationship of IDeltaT started just below 18 degrees C, and cooling temperature-responsive TG neurons from 20 degrees C resulted in an outward current, suggesting that IDeltaT is on at relatively low temperatures. Ion substitution and Ca2+ imaging experiments indicated that IDeltaT is primarily a monovalent cation current. IDeltaT was not sensitive to capsaicin or amiloride, suggesting that the current did not show similar pharmacology to other mammalian heat-sensitive membrane proteins. Our findings indicate that a novel temperature-sensitive conductance with unique ion permeability and low-temperature threshold is expressed in TG neurons and may be involved in highly sensitive heat detection in snakes.

Different intensities of high temperatures affect the growth of photosynthetic cells in nature. To elucidate the underlying mechanisms, we cultivated the unicellular green alga Chlamydomonas reinhardtii under highly controlled photobioreactor conditions and revealed systems-wide shared and unique responses to 24-hour moderate (35C) and acute (40C) high temperatures and subsequent recovery at 25C. We identified previously overlooked unique elements in response to moderate high temperature. Heat at 35C transiently arrested the cell cycle followed by partial synchronization, up-regulated transcripts/proteins involved in gluconeogenesis/glyoxylate-cycle for carbon uptake and promoted growth. But 40C disrupted cell division and growth. Both high temperatures induced photoprotection, while 40C distorted thylakoid/pyrenoid ultrastructure, affected the carbon concentrating mechanism, and decreased photosynthetic efficiency. We demonstrated increased transcript/protein correlation during both heat treatments and hypothesize reduced post-transcriptional regulation during heat may help efficiently coordinate thermotolerance mechanisms. During recovery after both heat treatments, especially 40C, transcripts/proteins related to DNA synthesis increased while those involved in photosynthetic light reactions decreased. We propose down-regulating photosynthetic light reactions during DNA replication benefits cell cycle resumption by reducing ROS production. Our results provide potential targets to increase thermotolerance in algae and crops.

Here's my issue: some of these temp table might have 100,000 rows or more in them while I use them for various calculations. Because of this I would like to generate indexes on the temp tables to keep performance up. And since these are temp tables that are created within a stored procedure, they need to have unique names to avoid errors if multiple users execute the sproc at the same time. I know that I can manually declare the temp tables using CREATE TABLE statements, and if I do that I can specify an index without a name and let SQL Server create the name for me. What I'm hoping to be able to do is use SELECT * INTO to generate the temp table and find another way to get SQL Server to auto-generate index names. I'm sure you're asking "Why?" My company has several changes in store for the system that I'm working with. If I can manage to use the SELECT INTO method, then, if a column gets added or resized or whatever, then there won't be an issue with the developers needing to know that they have to go back into these stored procedures and change their temp table definitions to match. Using SELECT INTO will automatically keep the temp tables matching the layout of the "real" tables. 17dc91bb1f