The efficient market hypothesis (EMH) cannot explain economic bubbles because, strictly speaking, the EMH would argue that economic bubbles don't really exist. The hypothesis's reliance on assumptions about information and pricing is fundamentally at odds with the mispricing that drives economic bubbles.

Economic bubbles occur when asset prices rise far above their true economic value and then fall rapidly. The EMH states that asset prices reflect true economic value because information is shared among market participants and rapidly incorporated into the stock price.

Key Takeaways

  • The efficient market hypothesis cannot explain economic bubbles since according to the theory, economic bubbles can't exist.
  • The EMH states that asset prices reflect their true economic value since information is shared among market participants and rapidly priced into the stock price.

Understanding Efficient Market Hypothesis

Efficient market hypothesis is a theory that holds the belief that stock prices are accurately priced and reflect all of the available information in the market. Efficient market hypothesis assumes that the market is efficient, meaning that investors have access to all of the necessary information to make informed investment decisions. As a result, outperforming the market is not possible since stocks are already accurately priced under EMH.

Under the EMH, there are no other factors influencing underlying price changes, such as irrationality or behavioral biases. In essence, then, the market price is an accurate reflection of value, and market bubbles are simply notable changes in the fundamental expectations about asset returns.

According to the efficient market hypothesis, there's no way for investors to identify value stocks or stocks that are trading at a cheaper price than what they're worth. Instead, if investors want to outperform the market, the only way they can achieve higher returns would be to purchase high-risk investments. However, investors such as Warren Buffett have been able to consistently outperform the overall market by identifying value stocks when they're unpopular with most investors.

Efficient Market Hypothesis and the Financial Crisis

Nobel Prize winning economist Eugene Fama is one of the pioneers of EMH. Fama has argued that the 2008-2009 financial crisis, in which credit markets froze, and asset prices dropped precipitously, was a result of the onset of a recession rather than the burst of a credit bubble. The change in asset prices reflected updated information about economic prospects.

The definition of a bubble is that the right price is fundamentally different from the market price, meaning that the consensus price is wrong. Fama has said that for a bubble to exist, it would have to be predictable, which would mean that some market participants would have to see the mispricing ahead of time. He argues that there is no consistent way to predict bubbles. Since bubbles can only be identified in hindsight, they cannot be said to reflect anything more than rapid changes in expectations based on new market information.

Efficient Market Hypothesis and Bubbles

Whether bubbles are predictable is subject to debate. Behavioral finance, a field that attempts to identify and examine financial decision making, has uncovered several biases in investment decision making, both on an individual and market level. There are several reasons why a market and investors could act inefficiently and as a result, misinterpret a bubble as a bull market.

Market Information

All investors review information differently and could, therefore, apply different stock valuations. Also, some investors might exhibit inattentiveness to certain kinds of information. For example, stock prices take time to respond to new information and the investors who act quickly on the information could earn more profit than those who act on the information later.

Human Emotions

Stock prices can be affected by human error and emotional decision making. Herding behavior is when all market participants act in the same way to the information available. The herd instinct could be applied to the correction in the S&P 500 following information about the 2020 coronavirus outbreak. Although the fear could be justified, the fear of losing money prompted many traders and investors to sell equities leading to widespread declines in markets across the globe.

Human Bias

Confirmation bias can occur when investors only accept and research information that supports their view of the investment. If an investor is bullish on a stock, only articles and research that support the bullish view would be considered. As a result, the investor might miss or avoid pertinent information that might cause the stock's price to decline. These biases have been shown to exist, but determining the incidence and level of a particular bias at a particular time has its challenges.

Special Considerations

Of course, it should be noted that the EMH doesn't demand that all market participants are right all the time. However, one of the theory's core tenets revolves around the idea of market efficiency. Given that market participants share the same information, the consensus price should accurately reflect an asset's fair value because those who are wrong transact with those who are right. Behavioral finance, on the other hand, argues that the consensus can be wrong.

Whether it is predictable or not, some have argued that the financial crisis represented a serious blow to the EMH because of the depth and magnitude of the mispricings that preceded it. However, proponents of efficient market hypothesis would likely disagree.


PRV cannot register a trademark if it contains something that can be perceived as some else’s distinctive surname.

This is applicable if the use of the trademark is a disadvantage to the bearer of the name and if it does not clearly refer to someone long since deceased.

The purpose of this provision is that the protection for surnames in the Trademarks Act does not extend beyond the protection according to the Names Act.

Does someone else have the surname?

For a distinctive surname to be the reason a trademark cannot be registered it has to be borne by someone else than the applicant.

The Names Act does not only protect identical names: a trademark must not be confusingly similar to a distinctive surname. For example, The Supreme Court have ruled that Gullmarsstrand is confusingly similar to Gullmarstrand and Vänerskog is confusingly similar to Wänerskog.

A surname used in Sweden has to be distinctive to be protected and the distinctiveness should be interpreted the same was as in the Names Act: a surname is distinctive if it indicates association to a certain family. However, the requirements for a distinctive surname has not yet been confirmed in practice.

Whether a name is distinctive or not is not only dependent on how many bearers the name has. A surname with many bearers may be distinctive, for example if it is associated with only a few families. If the surname is always associated with a particular family it is considered distinctive.

A disadvantage to the bearer

A registration of the trademark has to be a disadvantage to the bearer of the distinctive surname. Otherwise it is not a reason to not register the trademark. It is not enough reason to not want your name as someone else’s trademark.

In most cases PRV cannot determine if the use of the trademark would be a disadvantage to the bearer of the name. Therefore, the bearer must oppose to the registration and state the reasons the trademark is disadvantage to them personally.

There are cases where PRV has been able to assess whether the name being registered as a trademark would be a disadvantage to the bearer. We can for instance refuse an application with regards to a distinctive surname if the trademark in itself, or the goods and services in the application, is something that would apparently be offensive to be associated with.

It may also be a disadvantage if a trademark contains a well-known person’s distinctive surname and the intended use is related to the goods or services the person is well-known for.


You might feel silly, but it works. When Alan R. Hirsch, MD, neurological director of the Smell & Taste Treatment and Research Foundation in Chicago, tried this with 3,000 volunteers, he found that the more frequently people sniffed, the less hungry they were and the more weight they lost—an average of 30 pounds each. One theory is that sniffing the food tricks the brain into thinking you’re actually eating it.

Based on this, researchers from the University of Alabama conducted a study with a small group of obese men with prediabetes. They compared a form of intermittent fasting called “early time-restricted feeding,” where all meals were fit into an early eight-hour period of the day (7 am to 3 pm), or spread out over 12 hours (between 7 am and 7 pm). Both groups maintained their weight (did not gain or lose) but after five weeks, the eight-hours group had dramatically lower insulin levels and significantly improved insulin sensitivity, as well as significantly lower blood pressure. The best part? The eight-hours group also had significantly decreased appetite. They weren’t starving.
The ketogenic diet reduces seizure frequency by more than 50% in half of the patients who try it and by more than 90% in a third of patients.[18] Three-quarters of children who respond do so within two weeks, though experts recommend a trial of at least three months before assuming it has been ineffective.[9] Children with refractory epilepsy are more likely to benefit from the ketogenic diet than from trying another anticonvulsant drug.[1] Some evidence indicates that adolescents and adults may also benefit from the diet.[9]

You already know to get your dressing on the side because restaurants tend to drown salads with too much. But instead of pouring it on or even dipping the leaves in, do the “fork dip.” Stick the tongs of an empty fork into the dish of dressing before skewering any salad. You’ll be surprised by how much flavor you’ll get, but with way fewer calories. Next, check out these 30 tiny diet changes that can help you lose weight.
During the 1920s and 1930s, when the only anticonvulsant drugs were the sedative bromides (discovered 1857) and phenobarbital (1912), the ketogenic diet was widely used and studied. This changed in 1938 when H. Houston Merritt, Jr. and Tracy Putnam discovered phenytoin (Dilantin), and the focus of research shifted to discovering new drugs. With the introduction of sodium valproate in the 1970s, drugs were available to neurologists that were effective across a broad range of epileptic syndromes and seizure types. The use of the ketogenic diet, by this time restricted to difficult cases such as Lennox–Gastaut syndrome, declined further.[10]
The ketogenic diet is a high-fat, adequate-protein, low-carbohydrate diet that in medicine is used primarily to treat difficult-to-control (refractory) epilepsy in children. The diet forces the body to burn fats rather than carbohydrates. Normally, the carbohydrates contained in food are converted into glucose, which is then transported around the body and is particularly important in fueling brain function. However, if little carbohydrate remains in the diet, the liver converts fat into fatty acids and ketone bodies. The ketone bodies pass into the brain and replace glucose as an energy source. An elevated level of ketone bodies in the blood, a state known as ketosis, leads to a reduction in the frequency of epileptic seizures.[1] Around half of children and young people with epilepsy who have tried some form of this diet saw the number of seizures drop by at least half, and the effect persists even after discontinuing the diet.[2] Some evidence indicates that adults with epilepsy may benefit from the diet, and that a less strict regimen, such as a modified Atkins diet, is similarly effective.[1] Potential side effects may include constipation, high cholesterol, growth slowing, acidosis, and kidney stones.[3]

Work indulgence foods into your calorie plan. If you do want to have something that is a little higher in calories, then make sure that you work it into your overall calorie goal for the day. For example, if you are following a 1,800 calorie plan, and you want to have a brownie that is 300 calories, then you would only have 1,500 calories left for the day.
The Mayo Clinic Diet is designed to help you lose up to 6 to 10 pounds (2.7 to 4.5 kilograms) during the initial two-week phase. After that, you transition into the second phase, where you continue to lose 1 to 2 pounds (0.5 to 1 kilogram) a week until you reach your goal weight. By continuing the lifelong habits that you've learned, you can then maintain your goal weight for the rest of your life.


Microeconomics / Macroeconomics Theory Questions State Whether The Following Statements Are

Microeconomics / Macroeconomics Theory questions.

State whether the following statements are

True or False and Explain your answer.

P.S They are not linked to each other.

  • The introduction of a universal basic income would (other things being equal) unambiguously raise GDP in a New Keynesian model; but it would unambiguously lower GDP in a one-period competitive model.


Now： Home >>News >>行业新闻

DESBOER SAE bor precision planetary gear is introduced

Precision planetary reducer is another type of planetary gear reducer in the industry.

main transmission structure is: planet wheel, solar wheel, inner gear ring.
Compared with

other reducer, precision planetary reducer has the characteristics of high rigidity, high

precision (single stage can achieve less than 1 points), high transmission efficiency

(single stage in 97%-98%), high torque / volume ratio, life-long maintenance free and so

on. Most are mounted on stepping motors and servo motors to reduce speed, lift torque, and

match inertia.
Reduction ratio: input speed ratio, upper output speed.
Progression: the cycle

of planetary gears. Because a planetary gear can not meet the large transmission ratio,

sometimes two or three sets are needed to meet the requirements of the larger transmission

ratio of the user. Due to the increase in the number of planetary gears, the two or three

deceleration stages will increase in length and decrease in efficiency.
Full load

efficiency: refers to the maximum load (failure to stop the output torque), the

transmission efficiency of the reducer.
Average life: refers to the speed reducer at rated

load, the maximum input speed of the continuous working hours.
Rated torque: a standard for

speed reducers. At this value, when the output speed is 100 RPM / min, the life of the

reducer is average life. Over this value, the average life of the reducer will decrease.

When the output torque is more than two times the value, the reducer fault.
Lubrication: no

lubrication required. The reducer is fully sealed, so there is no need to add grease during

the whole service life.
Noise: the unit is decibel (dB). This value is measured at the input

speed of 3000 revolutions per minute, without load, from a meter distance of the reducer.
The return gap: the output end is fixed, the input end of the clockwise and counter

clockwise, the rated torque +-2% torque output, speed reducer input end has a tiny angular

displacement, the angular displacement is the return gap. Units are "points", that is, 1/60

of the time. The usual return gap value refers to the output of the reducer.


X-ray Vision Reveals the Insides of Stars
22 ביולי 2014
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You might have heard that much of the material making up the world around us was forged in the hot bellies of massive stars. But how do we know this? We can’t send probes to investigate because there isn’t a material on Earth that can withstand the immense heat inside a star without being vapourised.

Luckily for us (but not for the stars), every star over 8 times heavier than our Sun will eventually explode as a supernova. When this happens, all the star’s innards are launched into space for everyone to see. A supernova explosion also makes rare elements like Gold, Titanium and Uranium and can briefly outshine an entire galaxy!

Each of these four fabulous photographs shows the remains of an exploded star — called a supernova remnant. The pictures were released by NASA's Chandra X-ray Observatory to celebrate the telescope’s 15th birthday. Chandra is a telescope that is specially designed to look at X-rays that come from very hot places and objects in the Universe — including exploded stars. Because the explosions have super-heated these stellar wreckages, they glow very brightly in X-ray light.

Since the Earth’s atmosphere blocks X-rays from space, Chandra has to orbit high above it. It currently looks at the Universe from 140,000 km above the Earth. From this ideal position Chandra can create X-ray pictures with superb detail, allowing us to study the shape, movement and chemical make-up of supernova remnants.

Moving from left to right, the objects are The Crab Nebula, G292.0+1.8, Tycho’s Supernova and on the bottom is 3C58.

עובדה מעניינת

Supernova remnants don’t actually create any energy of their own, meaning their supply will eventually run out and each of these beautiful objects will fade away until they’re invisible. But don’t worry, they will last many thousands of years.

This Space Scoop is based on a Press Release from Chandra X-ray Observatory.
Chandra X-ray Observatory
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Protocol aware recovery for consensus-based storage

Protocol aware recovery for consensus based storage Alagappan et al., FAST’18

Following on from their excellent previous work on ‘All file systems are not created equal’ (well worth a read if you haven’t encountered it yet), in this paper the authors look at how well some of our most reliable protocols — those used in replicated state machines (RSM) — handle storage faults and corruptions. The report is not good:

Our analyses show that most approaches employed by currently deployed systems do not use any protocol-level knowledge to perform recovery, leading to disastrous outcomes such as data loss and unavailability.

Aren’t these protocols (such as Raft and Paxos) explicitly designed to ensure agreement and tolerate failed nodes? The gold standard that you reach for when dealing with the most critical data that needs strong durability and consistency guarantees? Yes they are, but you always have to pay attention to the failure model the system is designed for. Storage faults and data corruptions weren’t part of that failure model. Somebody forgot to tell that to the real world.

Having demonstrated the problem, the authors go on to design a new protocol-aware recovery approach.

To correctly recover corrupted data from redundant copies in a distributed system, we propose that a recovery approach should be protocol aware. A protocol-aware recovery (PAR) approach is carefully designed based on how the distributed system performs updates to replicated data, elects the leader etc..

Failure to be protocol-aware might lead, for example, to a node attempting to fix its data from a stale node, potentially leading to data loss. The solution is CTRL, corruption-tolerant replication. It comprises a local storage layer that can reliable detect faults, and a distributed protocol to recover from them using redundant copies. The authors won a best paper award at FAST’18 for their work.

What could possibly go wrong?

Inside a storage device, faults manifest as either block errors or corruptions. Block errors arise when the device internally detects a problem with a block and throws and error upon access. Corruption can occur due to lost and/or misdirected writes and may not be detected by the device. Some file systems (e.g. btrfs) can detect corruption and return an error to applications. (See also ccfs ). Others, such as ext4, simply silently return corrupted data if the underlying block is corrupted.

In either case, storage systems build atop local file systems should handle corrupted data and storage errors to preserve end-to-end data integrity.

Keeping redundant copies on each node is wasteful in the context of distributed systems where the data is inherently replicated.

Within a replicated state machine system, there are three critical persistent data structures: the log, the snapshots, and the metainfo. The log maintains the history of commands, snapshots are used to allow garbage collection of the log and prevent it from growing indefinitely, and the metainfo contains critical metadata such as the log start index. Any of these could be corrupted due to storage faults. None of the current approaches analysed by the authors could correctly recover from such faults.

The authors conducted both a theoretical and practical (fault-injection) analysis of real world systems including ZooKeeper, LogCabin, etcd, and a Paxos-based system, resulting in a taxonomy of current approaches.

The first group of responses are protocol oblivious, of which the most trivial is no have no detection strategy at all and just trust the underlying file system. Slightly better is to use checksums to detect corruptions and crash the node on detecting an error. (LogCabin, ZooKeeper, etcd all crash sometimes when their logs are faulty, ZooKeeper also crashes on corrupt snapshots). Crashing harms availability, so another strategy is to truncate the log at the point of detection of faulty data. Unfortunately this can also lead to silent data loss if the recovering node form a majority with other nodes that are lagging (demonstrated in ZooKeeper and LogCabin). A more severe form of truncate is to delete and rebuild all data. This can also lead to data loss in a similar way.

Surprisingly, administrators often use this approach hoping that the faulty node will be “simply fixed” by fetching the data from other nodes.

Some protocol aware strategies include mark non-voting as used by a Paxos-based system at Google (a faulty node deletes all data on fault detection, and marks itself as a non-voting member). This can lead to safety violations when a corrupted node deletes promises given to leaders. Reconfiguring involves removing the faulty node and adding a new one but again can harm availability if a majority are alive but one node’s data is corrupted. BFT should theoretically tolerate storage faults, but is expensive.

In short, when we consider the simple set of sample scenarios shows below, it turns out that none of the existing approaches exhibit correct behaviour in all of them.

Only CTRL is able to ensure safety and high availability under all six of these scenarios:

Corruption-tolerant replication

CTRL extends the standard RSM fault model for crash tolerant systems with a storage fault model including faults both in user data and in file-system metadata blocks.

CTRL guarantees that if there exists at least one correct copy of a committed data item, it will be recovered or the system will wait for that item to be fixed; committed data will never be lost.

It’s the job of the local storage layer (CLStore) to reliably detect faulty data on a node. CLStore also needs to be able to distinguish between crashes and corruptions as otherwise safety may be violated.

For logs, CLStore uses a modified log format which includes persistence records written in a different part of the media to the main entries. On a checksum mismatch, if a persistence record is not present, then we can conclude that the system crashed during an update. One special case is when the corrupted entry is the very last one in the log. In this case CLStore cannot disambiguate, and marks the record as corrupted leaving it to distributed recovery to fix or discard the entry based on global commitment.

For snapshots, CLStore splits them into chunks so that a faulty snapshot can be recovered at the granularity of individual chunks.

For metainfo (which is special in that it cannot be recovered from other nodes), CLStore simply maintains two local copies. Since metainfo is small and updated infrequently this does not incur significant overhead.

To ensure that a faulty item, once detected, can be reliably identified (what if the identifier in an entry is corrupt?) CLStore also redundantly stores the identifier of an item apart from the item itself. Faulty data items and their identifiers are passed to the distributed recovery layer for recovery using RSM-specific knowledge.

Since metainfo files are recovered locally, the distributed recovery layer is responsible for recovering log entries and snapshots.

Recovering log entries

If a leader has no faulty entries, then fixing a follower is straightforward – the leader can supply them to the follower. Things get more interesting when the leader itself discovers a fault. Now we could run a leader election with the constraint that a node cannot be elected leader if its log contains a faulty entry. However, in scenarios such as those shown in (b) below, this will lead to otherwise avoidable unavailability.

So we relax the constraint, and allow a node to be elected leader even if it has faulty entries. However, the leader must fix its faulty entries before accepting new commands.

The crucial part of the recovery to ensure safety is to fix the leader’s log using the redundant copies on the followers… However, in several scenarios, the leader cannot immediately recovery its faulty entries; for example, none of the reachable followers might have any knowledge of the entry to be recovered or the entry to be recovered might also be faulty on the followers.

Known uncommitted entries (determined for example by checking that a majority of followers do not have the entry) can be safely discarded. A known committed entry (because one of the followers has a commit record) can be recovered from the follower with the record. When commitment can’t be quickly determined (nodes down or slow), then the leader must wait for a response.

In the unfortunate and unlikely case where all copies of an entry are faulty, the system will remain unavailable.

Recovering snapshots

Current systems including ZooKeeper and LogCabin do not handle faulty snapshots correctly: they either crash or load corrupted snapshots obliviously. CTRL aims to recover faulty snapshots from redundant copies.

In current systems, every node runs the snapshot process independently, taking snapshots at different log indices. This makes recovery complex. CTRL ensures that nodes take snapshots at the same index — identical snapshots enable chunk-based recovery. The leader announces a snapshot index, and once a majority agree on it, all nodes independently take a snapshot at that index. Once the leader learns that a majority (including itself) of nodes have committed a snapshot at an index i, it garbage collects its log up to i, and instructs the followers to do the same.

A leader recovers its faulty chunks (if any) from followers, and then fixes faulty snapshots on followers.

Recovery technique summary

The following table summarise the techniques used by CTRL for storage fault recovery.

I’m running out of space for today’s post, so will have to give the briefest of treatments to the evaluation. If you’re in any doubt about the need for a system like CTRL though, it’s well worth digging into.

The following table shows the results for targeted corruption testing using LogCabin and ZooKeeper — both in their original form, and retrofitted with CTRL.

Whereas recovery is theoretically possible in 2401 cases, the original systems are either unsafe or unavailable in 2355 of these. CTRL correctly recovers in all 2401 cases.

With block corruptions the original LogCabin and ZooKeeper are unsafe in about 30% of cases. With block errors, they are unavailable in about 50% of cases. CTRL correctly recovers in all cases:

With snapshot faults CTRL correctly recovers from all cases. Original ZooKeeper always crashes the node leading to unavailability and potential loss of safety. LogCabin is incorrect in about half of all cases.

In the face of file system metadata faults (e.g., corrupt inodes and directory blocks) CTRL will reliable crash the node, preserving safety.

When using SSDs, the throughput overhead of CTRL is 4% in the worst case.

The last word

Our work is only a first step in hardening distributed systems to storage faults: while we have successfully applied the PAR approach to RSM systems, other classes of systems (e.g. primary-backup, Dynamo-style quorums) still remain to be analyzed. We believe the PAR approach can be applied to such classes as well. We hope our work will lead to more work on building reliable distributed storage systems that are robust to storage faults.


In 2003, a large group of young people from the nearby Canada Youth Conference (CY03) installed an outdoor amphitheatre in the green space between the Dove House and the House of the Prophet. This large open area has a wooden platform, log benches and a large cross anchored in a decades-old stone pile. Located in a natural depression called a kettle hole, it offers a quiet, secluded place for worship or events.


I forgot my password. How do I reset it?

There are two places to find your information.

The first place is in the initial email that you received after creating an account.

The other way is to go to the ‘Log in’ page on our website and click on ‘Lost your Username/Password?’ and follow the steps.

What this article helpful ? Yes or No


Something New

Happy, slowly feel your way.
Come soon to the day we play.
Rhyme a lot and pass the time.
Curl up close and start to climb.

In your sleep you dream away.
Passing through, it seems to sway.
Stop your heart on a dime.
Color, sketch and draw a line.

Can you see what is to come?
Feel vibrations as they strum.
Clouds descend then blow away.
Each new smile is a new day.

What will be is what will be.
Just accept and set it free.
Leave the other to spend a life.
Never wasting on more strife.

Catch a closing thought to picture.
Pull the edge and feel the friction.
Some time soon it all will end.
And your hardship start to bend.

Do you think it’s time to go?
If that is all, then maybe so.
Should we tarry to find our step?
Now it comes, nothing left.


leg cramps on keto

Why do some people experience leg cramps on keto? What could be causing these muscle spasms and how can you prevent it? Cramps are localized, involuntary muscle contractions that can be painful. They’re most common in the legs. Leg cramps can last several seconds or a few minutes. Most leg cramps are over in a few minutes [1].

Let’s delve into some possible reasons why this might happen and what you can do about it.

What Causes Muscle Cramps or Spasms on Keto?

People experience keto-related muscle spasms or leg cramps for several reasons, usually due to an essential mineral imbalance. The exact cause isn’t always clear and certain other general factors, such as insufficient blood flow, might also play a role [2].

1) Electrolyte Imbalance

When you reduce the carbohydrates in your diet, your body produces less insulin. The insulin hormone helps you process and store the sugar you eat and the foods that turn to sugar in your body (carbs). When you reduce the need for insulin, this triggers your kidneys to absorb less sodium, and more sodium is released in your urine. This can lead to sodium deficiency and electrolyte imbalance [3,4].

Electrolytes are positively charged minerals that fuel hundreds of bodily processes. Electrolytes include magnesium, sodium, potassium, and calcium. If your levels of these important electrolytes are depleted, your nerve cells might become more sensitive, leading to pressure on nerve endings that might cause muscle spasms [5,6]. Of all the electrolytes, low magnesium is also one of the most likely to cause muscle contractions and spasms.

benefits of sodium on keto

You might lose more electrolytes through urination when you’re adapting to the keto diet. This is in response to the decreased levels of blood sugar and the insulin hormone. The electrolyte loss is typically greater during the first 1-4 days of transitioning to the ketogenic diet, so keto-related muscle spasms are worse during this time.

2) Dehydration

Transitioning to the keto diet often results in increased urination due to certain factors, such as increased sodium excretion and reduced insulin levels. This increased urination can lead to dehydration — another possible cause of muscle spasm. Dehydration is a common keto side effect that might increase your risk of leg cramps, so make sure you’re drinking plenty of water and staying hydrated [7,8].

3) Caffeine!

Drinking too much coffee can increase your risk of getting leg cramps when you start keto since caffeine stimulates your muscles to contract. Caffeine is also a diuretic, so it helps take water out of your body, which can lead to muscle cramping and dehydration [9,10,11].

4) Exercising Without Hydrating

If you’re exercising, you lose both water and electrolytes in your sweat. Make sure you’re hydrated and getting sufficient electrolytes! [12].

5) Other Possible Causes

Other possible causes of muscle spasms that aren’t necessarily related to the ketogenic diet include certain medications, such as diuretics, statins, and asthma drugs, sedentary habits, strenuous physical activity, and medical conditions, such as kidney and liver failure [13,14,15].

Top Tips for Preventing Muscle Cramps on Keto!

Here are some useful tips for preventing muscle spasms on keto:

leg cramps on keto
  • Replenish your electrolytes with foods and supplements if needed
  • Consume bone broth
  • Salt your food to replenish sodium
  • Drink plenty of water and stay hydrated
  • Engage in gentle exercise and keep moving
  • Cut back on or avoid alcohol, caffeine, and other diuretics

On keto, you have a plethora of low-carb, electrolyte-rich foods to choose from. For example, for potassium, eat swiss chard, avocados, onions, spinach, tomatoes, mushrooms, and beet greens to rebalance your electrolyte levels. For magnesium, you can eat pumpkin seeds, cashews, Brazil nuts, arugula, kale, broccoli, and oysters [16,17].

If you have severe or persistent muscle spasms, you should visit your health care practitioner to rule out an underlying problem.

Do You Experience Leg Cramps or Muscle Spasms on Keto?

What are your top tips for preventing muscle spasms when transitioning to the ketogenic diet? How do you avoid the keto flu?

1)  Young, G. (2009). Leg cramps. British Medical Journal Clinical Evidence, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2907778/

2)  Paoli, A., Rubini, A., Volek, J. S., & Grimaldi, K. A. (2013). Beyond weight loss: A review of the therapeutic uses of very-low-carbohydrate (ketogenic) diets. European Journal of Clinical Nutrition, 67(8), 789-796. doi: 10.1038/ejcn.2013.116

3)  Tiwari, S., Riazi, S., & Ecelbarger, C. A. (2007). Insulin’s impact on renal sodium transport and blood pressure in health, obesity, and diabetes. American Journal of Physiology, 293(4), F974-F984. https://doi.org/10.1152/ajprenal.00149.2007

4)  Harvey, C. J., Schofield, G. M., & Williden, M. (2018). The use of nutritional supplements to induce ketosis and reduce symptoms associated with keto-induction: A narrative review. PeerJ, https://doi.org/10.7717/peerj.4488

5)  Shrimanker, I., & Bhattarai, S. (2020). Electrolytes. StatPearls, https://www.ncbi.nlm.nih.gov/books/NBK541123/

6)  Miller, K. C., Stone, M. S., Huxel, K. C., & Edwards, J. E. (2010). Exercise-associated muscle cramps. Sports Health, 2(4), 279-283. doi: 10.1177/1941738109357299

7)  Kang, H. C., Chung, D. E., Kim, D. W., & Kim, H. D. (2004). Early-and late-onset complications of the ketogenic diet for intractable epilepsy. Epilepsia, 45(9). 1116-1123. DOI: 10.1111/j.0013-9580.2004.10004.x

8)  Gupta, L., Khandelwal, D., Kalra, S., Gupta, P., Dutta, D., & Aggarwal, S. (2017). Ketogenic diet in endocrine disorders: A current perspectives. Journal of Postgraduate Medicine, 63(4), 242-251. doi: 10.4103/jpgm.JPGM_16_17

9)  Molema, M., Dekker, M. C. J., Voermans, N. C., Engelen, B. G. M., & Van Aarnoutse, R. E. (2007). Caffeine and muscle cramps: A stimulating connection. American Journal of Medicine, 120(8), 1-2. https://repository.ubn.ru.nl/handle/2066/52945

10) Polhuis, K. C. M. M., Wijnen, A. H. C., Sierksma, A., Calame, W., & Tieland, M. (2017). The diuretic action of weak and strong alcoholic beverages in elderly men: A randomized diet-controlled crossover trial. Nutrients, 9(7), doi: 10.3390/nu9070660

11) Delacour, C., Chambe, J., Lefebvre, F., Bodot, C., Bigerel, E., Epifani, L., Granda, C., Haller, D. M., & Maisonneuve, H. (2018). Association between alcohol consumption and nocturnal leg cramps in patients over 60 years old: A case-control study. 16(4), 296-301. DOI: 10.1370/afm.2238

12) Turner, M. J., & Avolio, A. P. (2016). Does replacing sodium excreted in sweat attenuate the health benefits of physical activity? International Journal of Sports Nutrition and Exercise Metabolism, 26(4), 377-389. DOI: 10.1123/ijsnem.2015-0233

13) Garrison, S. R., Dormuth, C. R., Morrow, Carney, G. A., & Khan, K. M. (2012). Nocturnal leg cramps and prescription use that precedes them: A sequence symmetry analysis. Archives of Internal Medicine, 172(2), 120-126. DOI: 10.1001/archinternmed.2011.1029

14) Hallegraeff, J., de Greef, M., Krijnen, W., & van der Schans, C. (2017). Criteria in diagnosing nocturnal leg cramps: A systematic review. BMC Family Practice, doi: 10.1186/s12875-017-0600-x

15) Maisonneuve, H., Chambe, J., Delacour, C., Muller, J., Rougerie, F., Haller, D. M., & Leveque, M. (2016). Prevalence of cramps in patients over the age of 60 in primary care: A cross sectional study. BMC Family Practice, doi: 10.1186/s12875-016-0509-9

16) World Health Organization. (2012). Guideline: Potassium intake for adults and children. https://www.ncbi.nlm.nih.gov/books/NBK132468/

17) Razzaque, M. S. (2018). Magnesium: Are we consuming enough? Nutrients, 10(12), doi: 10.3390/nu10121863

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A Very Short Introduction to R

The text you are reading now is actually created as an RMarkdown Notebook in RStudio. The best way to read this would be to open the notebook in RStudio and follow along, evaluating the code. You can get the notebook file here.

R code can be evaluated either by pressing Ctrl-Shift-Enter with the cursor inside some code or by pressing the little green arrow at the right margin of the code blocks.

On Getting Started with R you can read a short introduction on how to install R and RStudio.

Okay, so the aim of this short R walk-through is to show a path from basic R to running code on the DeIC Cultural Heritage Cluster at the Royal Danish Library (CHC)

Computer languages like R, that has been around for a long time, live through different styles and opinionated principles. One such principle is expressed by the Tidyverse which I like and advocate.

You enter the Tidyverse by loading the tidyverse library – almost. On a newly created R installation, you first need to install the libraries on your computer. This is done using the install.packages function in the following code part. Note that this is only nessecary once!

Then you can load the tidyverse and some other nessecary libraries for this tutorial.

library(rlist) # for list.filter
library(readr) # for write_csv and read_csv

The very basics of R

Standard operators, i.e. plus, minus and so on, work as we expect

2 + 2
## [1] 4

Naming values

Values can be stored for later re-use by giving them a name. Naming values is done with an arrow and it can be performed both to the left and to the right.

2 + 2         -> a_named_value
another_named_value <-  2 + 3

a_named_value + another_named_value
## [1] 9

To me, one of the things that R wonderfull to work with, is the pipe operator: %>%. This operator take what's on the left and sends it to whatever is on the right, e.g. "The Quick Brown Fox" %>% length calculates the length of the given sentence.

You enable the pipe operator by loading the magrittr library.

Okay, so what can we do with this pipe?

Let's say we have a string of words that we want to count. Evaluating such a sentence just gives us the same thing back:

"Gollum or Frodo And Sam"
## [1] "Gollum or Frodo And Sam"

To count elements in a list, i.e. the words in the sentence, we can use the length function:

"Gollum or Frodo And Sam" %>% length()
## [1] 1

Okay, so length recieves a list with one element: sentence. Let's split that sentence into words (observe that it's okay to break pipes into multiple lines):

"Gollum or Frodo And Sam" %>%
  str_split(" ", simplify = TRUE) %>%
## [1] 5

Now, the simplify = TRUE is needed because str_split can do a lot more that just split a sentence, but for now we just need the simple stuff.

Well, we're not content yet, as we don't want to count words like “or” and “and”. Such words are called stop words. In other words, we want to ignore words that belong to a list of stop words we define. In R, a list of words is defines thus:

c("or", "and")
## [1] "or"  "and"

If we want to know if a a word is contained in such a list, i.e. we want to ask whether “or” is in the list (“or”, “and”), we can do like this:

"or" %in% c("or", "and")
## [1] TRUE

But we really want to ask whether “or” is not in the list. In most computer languages, a truth or false statement can be reversed by the ! character.

## [1] TRUE

So, our list checking expression becomes

!("or" %in% c("or", "and"))
## [1] FALSE

Back to our word counting example. We can now filter the list of words using the above with the list.filter function

"Gollum or Frodo And Sam" %>%
  str_split(" ", simplify = TRUE) %>%
  list.filter(some_word ~ !(some_word %in% c("or", "and"))) %>%
## [1] 4

Four?! Well, as we should know, computers are stupid and don't understand that when we say “and”, we also mean “And”. This is remedied by one more part to the pipeline

"Gollum or Frodo And Sam" %>%
  tolower() %>%
  str_split(" ", simplify = TRUE) %>%
## [1] 3

Data in tables

Most data come in tables in one form or another. Data could be in an Excel spreadsheet, a csv file, a database table, an HTML table, and so on. R understands all these forms and can import them into an R data table, or data frame, as they are called in R.

A very easy way to create a data table or frame, is to use the tibble package, again part of the Tidyverse. The following function creates a data frame with two columns named letter_code and value:

  ~letter_code, ~value,
  "a", 2,
  "b", 3,
  "c", 4,
  "π", pi,
  "a", 9
## # A tibble: 5 x 2
##   letter_code value
##   <chr>       <dbl>
## 1 a            2
## 2 b            3
## 3 c            4
## 4 π            3.14
## 5 a            9

Let's do that again and also give the table a name

  ~letter_code, ~value,
  "a", 2,
  "b", 3,
  "c", 4,
  "π", pi,
  "a", 9
) -> some_data_frame

Data frames can be mutated, filtered, grouped etc. As an example, let's look at all the rows that have value greater than 3:

some_data_frame %>%
  filter(value > 3)
## # A tibble: 3 x 2
##   letter_code value
##   <chr>       <dbl>
## 1 c            4
## 2 π            3.14
## 3 a            9

Look at the same data in a visual way

some_data_frame %>%
  filter(value > 3) %>%
  ggplot() +
    geom_point(aes(x = letter_code, y = value))

plot of chunk unnamed-chunk-18

The ggplot2 library is the best plotting library for R. It can produce everything from simple plots to animations and high quality plots ready for publication. It's also a part of the Tidyverse.

Here is a plot that aggregates the values into letter_codes:

some_data_frame %>%
  ggplot() +
    geom_col(aes(x = letter_code, y = value))

plot of chunk unnamed-chunk-19

Getting ready for large scale

Okay, so let's take R code to the next level. R is normally developed and run on a desktop computer or laptop, but it can also run as a server with a web browser interface — and you can hardly tell the difference.

As stated in the introduction, the aim of this text is to show how to run R analysis on the Cultural Heritage Cluster. This cluster is primarily an Apache Spark cluster and off course R, through the Tidyverse, has an interface to such a Spark cluster.

Now, let's see how that works, but be aware: we're trying to break a butterfly upon a wheel…

First ensure that the package for the Spark integration is installed:

Now, sparklyr works up against two different Spark clusters. The one being a real cluster running on physical or virtual hardware in some server room and the other being a local pseudo cluster. The latter makes it easy for us to create the nessecary code for analysis before turning to the Real Big Thing.

Load the Spark library:

If you want to run against a local pseudo instance, do this, which installs Apache Spark on your machine.

spark_install(version = "2.1.0")
## Spark 2.1.0 for Hadoop 2.7 or later already installed.

The only difference for us is how to initiate the cluster, pseudo or not:

# Sys.setenv(SPARK_HOME='/usr/hdp/current/spark2-client') # for connecting to the CHC
# sc <- spark_connect(master = 'yarn-client')             # for connecting to the CHC
sc <- spark_connect(master = "local", version = "2.1.0")   # for connection to a local Spark
## Re-using existing Spark connection to local

Interlude: Get some data

Fetch the works of Mark Twain. Text mining with Spark & sparklyr) has a more in-depth example using this data.

Well, all of Mark Twains works are available at the Gutenberger project and R has an interface to that treasure trove.

# install.packages("gutenbergr") # evaluate if the package isn't installed already

Now, let's use the pipe operator and some functions from the gutenbergr package to fetch and store Mark Twain's writings. The expression takes a few minutes to complete.

gutenberg_works()  %>%
  filter(author == "Twain, Mark") %>%
  pull(gutenberg_id) %>%
  gutenberg_download() %>%
  pull(text) %>%

Okay, so what did we get?

readLines("mark_twain.txt", 20)
##  [1] "WHAT IS MAN? AND OTHER ESSAYS"
##  [2] ""
##  [3] ""
##  [4] "By Mark Twain"
##  [5] ""
##  [6] "(Samuel Langhorne Clemens, 1835-1910)"
##  [7] ""
##  [8] ""
##  [9] ""
## [10] ""
## [11] "CONTENTS:"
## [12] ""
## [13] "     What Is Man?"
## [14] ""
## [15] "     The Death of Jean"
## [16] ""
## [17] "     The Turning-Point of My Life"
## [18] ""
## [19] "     How to Make History Dates Stick"
## [20] ""

Load the texts onto Spark

Now, the texts are on the local file system, but we want it in Spark. Remember that we are breaking butterflies on wheels here!

twain <-  spark_read_text(sc, "twain", "mark_twain.txt")

The texts now has a copy in the Spark system, cluster, machine, or whatever we should call that thing. What's important is that we can use that copy for very large scale analysis. Here, we'll just do some very simple visualization.

First, let's get the data on a tidy form, i.e. remove all punctuation, remove stop-words and transform the text into a form with one word per row.

twain %>%

  filter(nchar(line) > 0) %>%
  mutate(line = regexp_replace(line, "[_\"\'():;,.!?\\-]", " ")) %>%

  ft_tokenizer(input.col = "line",
               output.col = "word_list") %>%

  ft_stop_words_remover(input.col = "word_list",
                        output.col = "wo_stop_words") %>%

  mutate(word = explode(wo_stop_words)) %>%
  select(word) %>%
  filter(nchar(word) > 2) %>%
  compute("tidy_words") -> tidy_words

That snippet of code does a lot:

  • The first filter function remove all empty lines (number of characters is more than zero)
  • the mutate function replaces all punctuation with spaces
  • the ft_tokenizer function tramsforms each line into a list of words
  • the ft_stop_words_remover removes a set of pre-defined stop words
  • the second mutate takes the list of words on each line a transforms that list into multiple rows, one per word
  • the select function removes all columns except the column with the word
  • the last filter function removes words with only one or two letters
  • the compute function stores the result in the Spark cluster for easy retrival later
  • and lastly save that Spark result as an R name called tidy_words

Count the word frequencies

Okay, so that can be used to perform a word count. The arrange function sorts a data frame, and the desc function gives us descending order, i.e. that largest number first. n is a implicit name created by the count function and n refers to the count of the thing counted in the count function.

tidy_words %>%
  count(word) %>%
  arrange(desc(n)) -> word_count

So, what were the ten most used words by Twain?

word_count %>% head(10)
## # Source:     lazy query [?? x 2]
## # Database:   spark_connection
## # Ordered by: desc(n)
##    word      n
##    <chr> <dbl>
##  1 one   20028
##  2 would 15735
##  3 said  13204
##  4 could 11301
##  5 time  10502
##  6 man    8391
##  7 see    8138
##  8 two    7829
##  9 like   7589
## 10 good   7534
## # ... with more rows

Show me the data

Again, a visualization gives some extra and we will now create a word cloud of Twain's words

word_count %>%
  arrange(desc(n)) %>%
  head(70) %>%
  collect() %>%
    colors = c("#999999", "#E69F00", "#56B4E9","#56B4E9")

plot of chunk unnamed-chunk-32

Next steps

And so on, towards ∞

Posted by Per Møldrup-Dalum in R, Tech

Getting Started with R

The DeIC National Cultural Heritage Cluster, the Royal Danish Library (CHC) has R as one of its two main interfaces, Python being the other one. R is very widespread in the data centric communities including the digital humanities. This blog post describes how to get started with R with the main objective of enabling the use of R at the CHC. Still, most of the descriptions here are generic and platform agnostic.

The R Project describes R in the following way:

R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R.

R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity.

R is available as Free Software under the terms of the Free Software Foundation’s GNU General Public License in source code form. It compiles and runs on a wide variety of UNIX platforms and similar systems (including FreeBSD and Linux), Windows and MacOS.

The R Project describes what is called the R environment in the following way

R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes an effective data handling and storage facility, a suite of operators for calculations on arrays, in particular matrices, a large, coherent, integrated collection of intermediate tools for data analysis, graphical facilities for data analysis and display either on-screen or on hardcopy, and a well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.

The term “environment” is intended to characterize it as a fully planned and coherent system, rather than an incremental accretion of very specific and inflexible tools, as is frequently the case with other data analysis software.

R, like S, is designed around a true computer language, and it allows users to add additional functionality by defining new functions. Much of the system is itself written in the R dialect of S, which makes it easy for users to follow the algorithmic choices made. For computationally-intensive tasks, C, C++ and Fortran code can be linked and called at run time. Advanced users can write C code to manipulate R objects directly.

Many users think of R as a statistics system. We prefer to think of it of an environment within which statistical techniques are implemented. R can be extended (easily) via packages. There are about eight packages supplied with the R distribution and many more are available through the CRAN family of Internet sites covering a very wide range of modern statistics.

We propose to use the RStudio platform for working with R. RStudio is a commercial organisation – developing tools and methods for and with R and their mission is:

RStudio has a mission to provide the most widely used open source and enterprise-ready professional software for the R statistical computing environment. These tools further the cause of equipping everyone, regardless of means, to participate in a global economy that increasingly rewards data literacy.

We offer open source and enterprise ready tools for the R computing environment. Our flagship product is an Integrated Development Environment (IDE) which makes it easy for anyone to analyze data with R. We also offer many R packages, including Shiny and R Markdown, and a platform for sharing interactive applications and reproducible reports with others.

Getting and installing R

As we propose to use RStudio for all things R, two things are needed: The R environment itself and the RStudio platform, where R is the language (end implementation) and RStudio is the workbench.

To download and install R, go to CRAN and select the package matching your platform. Windows, Linux, and macOS are all supported.

To download and install RStudio, go to RStudio Download and select the RStudio Desktop – Open Source License matching your operating system. Again all major systems are supported.

The first code

A very fine and highly recommended introduction to R and Data Science using R is the 2017 book R for Data Science by Hadley Wickham and Garrett Grolemund. This book is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 and can be read freely on the web or bought from O’Reilly.

Some notes on coding in R

As R is several decades old, a lot of R-code has been written using a lot of styles and principles and a lot of extension libraries that add functionality to the base of R. In recent years, the biggest movement within the R community has been the Tidyverse. The Tidyverse is, in their own words

R packages for data science

The tidyverse is an opinionated collection of R packages designed for data science.

All packages share an underlying design philosophy, grammar, and data structures.

The “tidy” in Tidyverse refers to an underlying principle on the structure on the data to be analyzed. In tidy data, each variable is a column, each observation is a row, and each type of observational unit is a table. This principle makes data much more easy to clean, explore, visualize, analyse, and so on. An in-depth description of, and argumentation for, the tidy data principle, can be found in Tidy data by Hadley Wickham (also published in The Journal of Statistical Software, vol. 59, 2014).

Oh, and Hadley Wickham has written a R style guide.

So, the Tidyverse contains libraries for creating and manipulating tidy data, but also tools for writing and communicating code and results. From interactive notebooksbook writing systems, and interactive web applications, all at your R-enabled fingertips.

Further reading

When finished with R for Data Science, a next logical step could be another R book under the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 license:

Text Mining with R by Julia Silge and David Robinson

Advanced R by Hadley Wickham

Communities and online resources

If you want to learn R, make it habit of visiting R-bloggers with daily news and tutorials about R, contributed by over 750 bloggers.

The R community is also very active on Twitter, where most R tweets are tagged with #rstat. Some important tweeters are:

  • Hadley Wickham hadleywickham is the main author of a lot of the Tidyverse (Not so long ago it was actually called the Hadleyverse) and ggplot, the primary plotting library for R. He is also the author of the books R for Data Science and Advanced R Programming
  • Mara Averick dataandme tweets a lot on everything R and does so in a fun and entertaining way.
  • The dane Thomas Lin Pedersen thomasp85 tweets a lot on data visualisering and is the author on a lot of very interesting R packages.

Posted by Per Møldrup-Dalum in R, Tech


[vc_row][vc_column width=”3/4″][vc_column_text]

wine-ansonicaThe charming medieval town of Gradoli rises on a spur in the Alta Tuscia overlooking the northern side of the Bolsena Lake. So technically it isn’t in the Maremma, but when it comes to the Aleatico di Gradoli, technicalities are unimportant.

The Aleatico is a beautifully mild red wine introduced into the area by the Etruscans who got the secrets of wine making from the Greeks. Legend has it that a demon lived in a cave just outside of Gradoli. One day, the demon came home to find a lion asleep in its cave. He tried to wake him, but the lion attacked and killed the demon. Only his staff remained and it grew into a screw. Eternally gratefully, the locals put the lion and the screw on their coats of arm. The screw is now known as the screw of Aleatico and is this wine’s namesake.

The Aleatico di Gradoli recieved DOC recognition in 1972. It’s produced in Gradoli and in Grotto di Castro, San Lorenzo Nuovo and Latera, all of which sit on the banks of the Bolsena Lake. The Aleatico is only found in this part of the peninsula because it needs the near perfect microclimate of the Bolsena Lake to get its the unique characteristics.

It’s produced in three different typologies: Aleatico di Gradoli, Aleatico di Gradoli Liquoroso and Aleatico di Gradoli Liquoroso Reserve.

Visual characteristics: An intense garnet red colour with violet tonalities

Olfactory characteristics: Fruity and delicately aromatic

Taste characteristics: Soft, velvety and sweet. A minimum alcohol graduation of 12°

Food pairings: Perfect with sweets that are made with hazelnuts, like those typical of Viterbo, as well dry pastries and tarts with red fruits

Visual characteristics: An intense garnet red with violet reflections

Olfactory characteristics: Particularly aromatic and delicate on the nose

Taste characteristics: Soft, warm and sweet. The minimum alcohol graduation is 17.5° with a compulsory ageing period of 6 months from the date of fortification

Food pairing: Fantastic as a meditation wine, it goes well with dry sweets, cakes with chocolate or hazelnuts and sweets made with red fruits

Visual characteristics: A very intense garnet red colour with a tendency to develop orange reflections with age

Olfactory characteristics: Strong aromatic aromas and characteristics of barrel ageing

Taste characteristics: Rounded, sweet, more or less tannic, but extremely palatable. The minimum alcohol graduation is 17.5° with compulsory ageing beginning from the date of fortification to two years in oak barrels with a maximum capacity of 250 litres. This is followed by a minimum bottle ageing of a year.

Food pairing: Best enjoyed with dry pastries, cakes with hazelnuts and chocolate and tarts of blackberries or raspberries. Ideal with just a piece of chocolate, especially if it’s dark. Great as a meditation wine.[/vc_column_text][/vc_column][vc_column width=”1/4″][templatera id=”10814″][/vc_column][/vc_row]


Children frequently receive unnecessary medical care regardless of insurance type

January 7, 2020 , University of Michigan
Credit: CC0 Public Domain

Children with public insurance are slightly more likely to receive medical services that they don't need than those with private insurance, a new study finds.

One in 11 publicly insured and one in nine privately insured children received in 2014, according to the findings published in journal Pediatrics.

Researchers evaluated data for 8.6 million children in 12 states to see whether having public or is associated with receiving low-value .

"In a prior study, we showed that privately insured children frequently received low-value services that do not improve their health, but we didn't know if publicly insured children were more or less likely to receive wasteful care," says lead author Kao-Ping Chua, M.D., Ph.D., a pediatrician and researcher at Michigan Medicine's C.S. Mott Children's Hospital and the Susan B. Meister Child Health Evaluation and Research Center.

"While we found that publicly insured children were a little more likely to receive low-value services, the difference was not large. The more important finding is that children are highly likely to receive wasteful care regardless of what type of insurance they have. This means that efforts to reduce waste should be global in nature and target the care of all children."

Researchers estimated the prevalence of 20 low-value diagnostic tests, imaging tests, and , such as unnecessary vitamin D screening, imaging for acute sinus infections, and for colds.

Among publicly and privately insured children in the sample, respectively, 11% and 9% received unnecessary services at least once in 2014 while about 4% and 3% received low-value services at least twice.

About 1 in 33 publicly and privately insured kids received a low-value diagnostic test at least once in 2014. About 1 in 12 publicly insured and 1 in 20 privately insured children received a low-value prescription drug at least once.

"Our study shows that insurance type doesn't strongly predict whether a child is likely to receive wasteful care," says Chua, who's also a researcher at the University of Michigan Institute for Healthcare Policy and Innovation.

Chua points to several factors that may explain why some children still receive low-value services despite evidence that they don't work. High on the list is the difficulty in changing the interventionist culture of medicine.

"Parents understandably want to relieve their children's suffering and to rule out serious problems," Chua says. "Both parents and doctors sometimes have a tendency to believe that prescribing a drug or ordering a test is better than doing nothing, even though the right answer is often to do less.

"The expectation that something be done can be particularly high when parents miss work and children miss school to go to the doctor, or when children previously received an unnecessary intervention for the same condition, like an antibiotic for a cold."

Some interventions also stem from an overabundance of caution.

"Doctors have a strong fear of missing something," Chua says. "Some doctors would rather over-treat and risk the side effects of the intervention than undertreat and risk missing a catastrophic problem."

Unnecessary care has consequences, Chua says. Overuse of antibiotics, for example, can increase antibiotic resistance and the risk of allergic reactions. MRIs sometimes expose to the risks of sedation while CT scans expose them to radiation, which can increase the lifetime risk of cancer.

All low-value services also come with wasteful healthcare spending, Chua says.

"These interventions waste healthcare dollars that could be devoted to other valuable causes, and also force many families to pay out-of-pocket for unnecessary care," Chua says. "Reducing wasteful care will improve child health and decrease the financial burden of health care spending on society and families."

Journal information: Pediatrics

Provided by University of Michigan


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Amoeba (1 fl oz)

Amoeba is for the temporary relief of symptoms related to amoeba infestation including consequent weakness, fever, and stomach cramps.

600 drops per bottle
Active Ingredients:
Baptisia (3X) Cajuputum (3X) Capsicum (3X) Fragaria (3X) Frasera Caroliniensis (3X) Hamamelis (3X) Quassia (3X) senna (3X) Hydrastis (6X) Ipecac (6X) Hepar Suis (8X) Pancreas (8X) Spleen (8X) Cinchona (12X) Iridium (12X) Lycopodium (12X)
Nitricum Acidum (12X) Nux Vomica (12X) Selenium (12X)
Blastocystis hominis (12C 3C 60C 200C) Cryptosporidium parvum (12C 3C 60C 200C) Entamoeba Histolytica (12C 3C 60C 200C) Giardia Lamblia (12C 3C 60C 200C)
Brugia Malayi (39C 60C 200C)
Inactive Ingredients:
Demineralized water, 25% Ethanol

1 to 10 drops under the tongue, 3 times per day, or as directed by your healthcare professional. Consult a physician for use in children under 12 years of age.

Keep out of reach of children.  If pregnant or breast-feeding, ask your healthcare provider before use.

Store in a cool, dry place (59°F-85°F) away from direct light.  Keep out of reach of children.


Why Am I So Tired?

Periodic fatigue is normal. It’s natural, and dare say it, it’s common.

Chronic fatigue, on the other hand, is much more insidious, invading our everyday life and causing other problems like brain fog, malaise, and lack of motivation. The general lack of energy that comes from fatigue might be physical, mental, emotional, or a mix of all three.

Fatigue is one of the top reasons why pole dancers get injured or take breaks from pole.

There are, unfortunately, a very wide range of possibilities that may be contributing to feeling fatigued, such as overtraining, pregnancy, inadequate sleep, stress, anxiety, depression, diabetes, anemia…

The list can go on for a mile.

For pole dancers, however, the impact is most often felt the most during training sessions, especially if you’re running out of stamina in the middle of routines, or feeling a lack of motivation to get on the pole in the first place.

Pole is our source of joy, it’s love, and the highlight of the day for many of us.

It’s not a helpless cause – just because you’re feeling fatigued doesn’t mean it’s the end of the line.

In this article, we cover some of the more common ways you can deal with (and reverse) fatigue, regain your energy levels, and start feeling that spark of joy again.

Eat More Often (and Healthier)

Eating fuels your body.

There’s no secret there.

A lack of suitable food can greatly impact your energy levels throughout the day, especially if you don’t eat often enough.

Eating more often can help you sustain energy levels (1) because you’re not allowing your blood sugar to fluctuate harshly up and down, and no crash means no loss in energy.

When you start giving your body what needs, cutting out junk, and paying attention to what goes in your body, you’ll be astonished by how junk food starts to lose its appeal in lieu of healthier foods.

Start portioning your meals.

You might find the idea silly – portioning meals, really? Right after you just said to eat more often? – but it’s not a suggestion to cut down on what you eat, just how much you eat at one time. By tracking what you eat throughout the day, you’ll be able to better asses where your macros (carbs, fat, and protein) are currently and where they need to be according to your lean mass and weight.

Always eat before pole class.

Skipping a meal before class will lead to a definite lack of energy throughout the rest of the day that can be hard to shake.

You never want to pole dance hungry because all it accomplishes is putting your body into a sort of “starvation mode” where it will store fat, cause fatigue, and increase your risk for injuries as your body looks for shortcuts in the movement to save energy.

Maintain a healthy relationship with food

Always remember to maintain a healthy relationship with your food, no matter what you’re eating. Food is fuel for your body and it’s critical to keep it healthy for your emotional and mental state as well.

Eating something that isn’t considered “healthy” is no reason to feel guilty. Put cheat days in place so you guarantee you stuff your face with as much junk as possible on one day a week, if you have to.

Don’t deny yourself that piece of chocolate if you’re on your monthly. Don’t berate yourself for wanting dessert after your dinner out with family.

You don’t have to eat “rabbit food” even if you decide to go (or are) vegan. There’s more to life than plain lettuce and dry nuts as a meal.

Want to make a salad? Go for a mix of mustard greens, spinach and kale with cranberries, walnuts, cheese (or faux-cheese) crumbles, diced boiled eggs, carrot slices, beets, and a nice balsamic vinaigrette.

That’s a salad.

Trying to eat healthy means you just get a different variety of delicious, hearty meals.

It’s not a diet – don’t think of it like that.

Nor is it a weight-loss regimen.

It’s your body. Your health.

It’s self-care.

Get Better Sleep for Better Pole Dance Progress

As humans, we have a circadian rhythm that helps our bodies produce melatonin when it gets dark so we can naturally fall asleep with the sun and get up with the sun.

This is a bit harder to do in today’s modern era where we use electric lights to extend our days and wake up mid-morning to look at the notifications on our phone.

While we are sleeping, however, each sleep cycle is typically in 90-minute intervals. Each of these cycles contain five different stages of sleep. Having a consistent bedtime and wake up time that coincides with those 90-minute interval cycles will leave you feeling more energized throughout the day.

Pay Attention to Your Individual Circadian Rhythm

Would you believe that each you have an individual circadian rhythm? (2)

It makes sense, when you consider that some of us are night owls and others are morning larks.

When do you have the most energy during the day? When you have a good night’s sleep, what time of day do you shine the brightest?

If you’re able to sync your sleep schedule with your own individual circadian rhythm, you’ll be surprised at how incredible you feel during the day in comparison to forcing yourself awake at a “normal” time.

Reduce Stress to Increase Your Gains

Emotional exhaustion is a very real problem, especially if you tend to overwork yourself at the job, or if you’re going through a particularly tough time in your life.

These feelings can come all at once or build up over a period of time. If you don’t have an outlet for this stress, you’ll overload your body.

Fatigue is a symptom of consistently high stress.

You can reduce stress by practicing self-care. Take some leisure time and read a book, take yourself out on a date, whatever makes you happy:

Soak in a bath and pamper yourself in ways you might not normally, like taking extra time to add bubbles to the bath, giving yourself a thorough shave, or mindfully lotioning your skin – with glycerine-based lotion, of course! Learn more about how lotion affects your skin in pole dancing here.

Cut the Caffeine and Alcohol

There’s plenty of evidence that suggests that caffeine (3) and alcohol can greatly affect your levels of fatigue, effectively “borrowing energy” from your body later to give it to you now. This is part of why you tend to crave caffeine or alcohol a little after ingesting some; the body is looking for that spike of energy again, but simply continues to borrow more and more from your body later.

“Caffeine actually aggravates adrenal exhaustion and low blood sugars, amplifying the anxiety and stress symptoms [of] fatigue.”

- Dr Teitelbaum MD

Medical Director of the National Fibromyalgia and Fatigue Centers

Alcohol might make you feel drowsy, and it most certainly is a sedative, but among many other symptoms post-hangover, it also disrupts the chemicals involved in a good night’s rest, meaning that you might get plenty of time to sleep, but your body hasn’t properly recovered during the night, so you’ll just feel more worn down the following few days, even if you just had one drink.

Drink More Water

Water fuels the body, greases the grooves, and allows your body to function better overall.

Maybe it’s not terribly surprising, but dehydration can cause or exacerbate fatigue.

What many people don’t know is that you might not even feel dehydrated if you don’t have enough water in your body. If your body isn’t absorbing the water, then your body isn’t receiving the benefits.

Make sure you’re getting enough water for your weight and activity level. Many people drink as little as one glass of water per day, whereas the average adult male needs about 3.7 litres of water, and 2.7 litres for women.

This, of course, doesn’t take into account any sort of intense or rigorous physical activity, like if you were training for a pole dancing competition or going to multiple pole classes each week.

A good rule of thumb is to half your body weight and drink one ounce of water per pound.

For example, if you weigh 120 pounds (54.4 kg), then you would half your body weight to get 60 lbs (27.2 kg.)

That would mean that someone who weighs 120 pounds should drink about 60 ounces, or 1,774 ml of water each day.

Get Plenty of Vitamins

Fatigue can easily be caused by a lack of proper nutrition, and while taking vitamins is never fun, it will make you feel much better during the day.

Consider taking a complete multivitamin for your gender and age range.

If you’re training for a pole competition or looking to put on some muscle, you might want to consider adding extra supplements like creatine, which is a natural substance found in your muscles that helps improve exercise performance by providing your muscles with more energy. (4)

Get Your Cardio On

If your pole sessions are a simple warm up followed by tricks or transitions, then a cool down, then it’s not enough for a balanced, health exercise regimen.

Your body might strong as all get out on the outside, but the heart itself is still a muscle and tends to be forgotten in favor of strengthening the rest of the body.

If you find yourself without the stamina to complete your routines or running out of breath during a mild exercise in pole class, then chances are, you need a little more cardio in your life.

A high resting heart rate is also a likely indicator of needing more cardio and can cause your body to sweat more – which means you’re more likely to slip off the pole.

Consider adding a sprint around your neighborhood block to your daily routine, or try cycling – or get in on some pole cardio routines!

1, SHN Staff, Sugar crash effects and how to fix them, retrieved from https://news.sanfordhealth.org/healthy-living/sugar-crash-effects/
2, Division of Sleep Medicine at Harvard Medical School, Individual Variation and the Genetics of Sleep, retrieved from http://healthysleep.med.harvard.edu/healthy/science/variations/individual-variation-genetics
3, Everyday Health, Can Caffeine Relieve Your Chronic Fatigue?, retrieved from https://www.everydayhealth.com/chronic-fatigue-syndrome/relief-with-caffeine.aspx
4, Healthline, Creatine 101 – What Is It and What Does It Do?, retrieved from https://www.healthline.com/nutrition/what-is-creatine#what-it-is