This Is What Happens to the Brain When You Give Up Sugar for Lent

Summary: Decided to cut back on sugary treats? A new article considers why it might not be such a sweet idea for all.

Source: The Conversation.

Anyone who knows me also knows that I have a huge sweet tooth. I always have. My friend and fellow graduate student Andrew is equally afflicted, and living in Hershey, Pennsylvania – the “Chocolate Capital of the World” – doesn’t help either of us.

But Andrew is braver than I am. Last year, he gave up sweets for Lent. I can’t say that I’m following in his footsteps this year, but if you are abstaining from sweets for Lent this year, here’s what you can expect over the next 40 days.

Sugar: natural reward, unnatural fix

In neuroscience, food is something we call a “natural reward.” In order for us to survive as a species, things like eating, having sex and nurturing others must be pleasurable to the brain so that these behaviours are reinforced and repeated.

Evolution has resulted in the mesolimbic pathway, a brain system that deciphers these natural rewards for us. When we do something pleasurable, a bundle of neurons called the ventral tegmental area uses the neurotransmitter dopamine to signal to a part of the brain called the nucleus accumbens. The connection between the nucleus accumbens and our prefrontal cortex dictates our motor movement, such as deciding whether or not to taking another bite of that delicious chocolate cake. The prefrontal cortex also activates hormones that tell our body: “Hey, this cake is really good. And I’m going to remember that for the future.”

Not all foods are equally rewarding, of course. Most of us prefer sweets over sour and bitter foods because, evolutionarily, our mesolimbic pathway reinforces that sweet things provide a healthy source of carbohydrates for our bodies. When our ancestors went scavenging for berries, for example, sour meant “not yet ripe,” while bitter meant “alert – poison!”

Fruit is one thing, but modern diets have taken on a life of their own. A decade ago, it was estimated that the average American consumed 22 teaspoons of added sugar per day, amounting to an extra 350 calories; it may well have risen since then. A few months ago, one expert suggested that the average Briton consumes 238 teaspoons of sugar each week.

Today, with convenience more important than ever in our food selections, it’s almost impossible to come across processed and prepared foods that don’t have added sugars for flavour, preservation, or both.

These added sugars are sneaky – and unbeknown to many of us, we’ve become hooked. In ways that drugs of abuse – such as nicotine, cocaine and heroin – hijack the brain’s reward pathway and make users dependent, increasing neuro-chemical and behavioural evidence suggests that sugar is addictive in the same way, too.

Sugar addiction is real

“The first few days are a little rough,” Andrew told me about his sugar-free adventure last year. “It almost feels like you’re detoxing from drugs. I found myself eating a lot of carbs to compensate for the lack of sugar.”

There are four major components of addiction: bingeing, withdrawal, craving, and cross-sensitisation (the notion that one addictive substance predisposes someone to becoming addicted to another). All of these components have been observed in animal models of addiction – for sugar, as well as drugs of abuse.

A typical experiment goes like this: rats are deprived of food for 12 hours each day, then given 12 hours of access to a sugary solution and regular chow. After a month of following this daily pattern, rats display behaviours similar to those on drugs of abuse. They’ll binge on the sugar solution in a short period of time, much more than their regular food. They also show signs of anxiety and depression during the food deprivation period. Many sugar-treated rats who are later exposed to drugs, such as cocaine and opiates, demonstrate dependent behaviours towards the drugs compared to rats who did not consume sugar beforehand.

Like drugs, sugar spikes dopamine release in the nucleus accumbens. Over the long term, regular sugar consumption actually changes the gene expression and availability of dopamine receptors in both the midbrain and frontal cortex. Specifically, sugar increases the concentration of a type of excitatory receptor called D1, but decreases another receptor type called D2, which is inhibitory. Regular sugar consumption also inhibits the action of the dopamine transporter, a protein which pumps dopamine out of the synapse and back into the neuron after firing.

Image shows candy sprinkles on a woman's lips.

There are four major components of addiction: bingeing, withdrawal, craving, and cross-sensitisation (the notion that one addictive substance predisposes someone to becoming addicted to another). All of these components have been observed in animal models of addiction – for sugar, as well as drugs of abuse. NeuroscienceNews.com image is adapted from the The Conversation article.

In short, this means that repeated access to sugar over time leads to prolonged dopamine signalling, greater excitation of the brain’s reward pathways and a need for even more sugar to activate all of the midbrain dopamine receptors like before. The brain becomes tolerant to sugar – and more is needed to attain the same “sugar high.”

Sugar withdrawal is also real

Although these studies were conducted in rodents, it’s not far-fetched to say that the same primitive processes are occurring in the human brain, too. “The cravings never stopped, [but that was] probably psychological,” Andrew told me. “But it got easier after the first week or so.”

In a 2002 study by Carlo Colantuoni and colleagues of Princeton University, rats who had undergone a typical sugar dependence protocol then underwent “sugar withdrawal.” This was facilitated by either food deprivation or treatment with naloxone, a drug used for treating opiate addiction which binds to receptors in the brain’s reward system. Both withdrawal methods led to physical problems, including teeth chattering, paw tremors, and head shaking. Naloxone treatment also appeared to make the rats more anxious, as they spent less time on an elevated apparatus that lacked walls on either side.

Similar withdrawal experiments by others also report behaviour similar to depression in tasks such as the forced swim test. Rats in sugar withdrawal are more likely to show passive behaviours (like floating) than active behaviours (like trying to escape) when placed in water, suggesting feelings of helplessness.

A new study published by Victor Mangabeira and colleagues in this month’s Physiology & Behavior reports that sugar withdrawal is also linked to impulsive behaviour. Initially, rats were trained to receive water by pushing a lever. After training, the animals returned to their home cages and had access to a sugar solution and water, or just water alone. After 30 days, when rats were again given the opportunity to press a lever for water, those who had become dependent on sugar pressed the lever significantly more times than control animals, suggesting impulsive behaviour.

These are extreme experiments, of course. We humans aren’t depriving ourselves of food for 12 hours and then allowing ourselves to binge on soda and doughnuts at the end of the day. But these rodent studies certainly give us insight into the neuro-chemical underpinnings of sugar dependence, withdrawal, and behaviour.

Through decades of diet programmes and best-selling books, we’ve toyed with the notion of “sugar addiction” for a long time. There are accounts of those in “sugar withdrawal” describing food cravings, which can trigger relapse and impulsive eating. There are also countless articles and books about the boundless energy and new-found happiness in those who have sworn off sugar for good. But despite the ubiquity of sugar in our diets, the notion of sugar addiction is still a rather taboo topic.

Are you still motivated to give up sugar for Lent? You might wonder how long it will take until you’re free of cravings and side-effects, but there’s no answer – everyone is different and no human studies have been done on this. But after 40 days, it’s clear that Andrew had overcome the worst, likely even reversing some of his altered dopamine signalling. “I remember eating my first sweet and thinking it was too sweet,” he said. “I had to rebuild my tolerance.”

And as regulars of a local bakery in Hershey – I can assure you, readers, that he has done just that.

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Source: Jordan Gaines LewisThe Conversation
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Celebrating the life of doctoral student and alumnus Michael B. Cohen

Michael B. Cohen ’14, SM ’16 had a deep love for mathematics and the theoretical foundations of computing — a love that was infectious, brilliant, and always shared with others. Cohen, a doctoral student in the Department of Electrical Engineering and Computer Science (EECS), died suddenly from natural causes in September. He was 25 years of age.

At the time of his passing, Cohen was visiting the University of California at Berkeley, where he had gone to meet with colleagues at the Simons Institute for the Theory of Computing. A member of the Theory of Computing group at the Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT, he had roots in the Washington area.

Daniela Rus, the Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science and Director CSAIL, said, “We are all still stunned by the news of the passing of Michael Cohen. Michael was a beloved student at CSAIL, a brilliant colleague in the theory group, and a joyful presence everywhere he went. This is a huge and collective loss for the entire CSAIL community.”

Cohen first came to MIT as an undergraduate student, and he lived in East Campus. He earned his bachelor’s in mathematics in 2014, having skipped his second year at MIT to work at Facebook. He then stayed on at MIT to pursue a graduate degree in computer science.

Scott Aaronson, a professor of computer science at the University of Texas at Austin who taught at MIT from 2007 to 2016, recalled Cohen as a particularly motivated first year student, ready to solve open problems, or basically tackle anything.

Writing on his blog, Aaronson noted that when he met Cohen he realized at once that he “was a freshman who I could — must — talk to like an advanced grad student or professor.” In his class on quantum complexity theory, Cohen had the habit of sitting in the front row and carrying on dialogues with Aaronson, often catching any errors or “unjustified claims.” At the same time, Aaronson was impressed by Cohen’s intellectual humility, as his focus was on understanding and clarifying tough concepts for everyone in the class, not showing off. Such openness led to Cohen “having a huge circle of friends.”

His fellow MIT students described him as “energetic, fun, and supportive,” and admired his irrepressible spirit of “exuberance and generosity.” Cameron Musco, a doctoral student in the same lab as Cohen and a frequent co-author, wrote, “It was impossible to ignore his energy, wonder, and excitement for research, current events, and everything in between.” Cohen was a notable presence on the 5th and 6th floors of the Stata Center at MIT, Musco also recalled, “always … surrounded by a group of friends happy to banter or simply to listen. He was a natural teacher — truly kind, humble, welcoming, positive, and always willing to slow his thoughts for a moment to share his brilliance.”

Cohen was an intellectual tour-de-force beyond the campus as well. He spent a summer at Microsoft Research, where he quickly cemented a reputation for “his larger-than-life personality” and academic brilliance. A statement by the team he worked with at Microsoft read: “Michael was a brilliant mathematician and a rising star in his field. … [H]e made sweeping progress in online learning and online algorithms, two fields he had just recently become acquainted with. In addition to solving five open problems in these areas, he continued his substantial progress on the k-server problem, one of the most celebrated and notoriously difficult challenges in the space of adaptive algorithms.”

Sebastien Bubeck, a researcher in the Theory Group at Microsoft Research who worked alongside Cohen, shared what he called a “typical Michael story,” about when they first met in October 2016 at MIT: “We were about to start lunch with a small group of graduate students and Michael entered the room, he (gently) interrupted the conversation and his first sentence to me was a question about mirror descent that I was not able to answer. (We now know the answer, and as it turns out his question was pretty deep and the answer highly non-trivial.)”

Bubeck, like many others, was also struck by Cohen’s remarkable way of doing mathematics, primarily never writing anything on paper. James R. Lee, a professor of computer science at University of Washington, said, “His mind was always going at 100 mph, so it was remarkable that he didn’t miss a beat in calibrating (i.e., slowing down) for an audience (or for those who did not know him).”

Luca Trevisan, a professor of electrical engineering and computer science at Berkeley, noted that “in a few short years, Michael left his mark on a number of problems.” At the time of his death, Cohen was credited as a co-author on papers with more than 30 distinct collaborators. Tom Cohen, Michael’s father, remarked that his son, “more than anything, wished to become part of that community and to engage in a meaningful way on relevant research in the field.” Cleary, he achieved that and much more, becoming a leading light in the theoretical computer science community.

As Lee wrote, “one got the sense that this was all a warmup for Michael. It’s really disheartening that we won’t get to see what comes next.” He and others have committed to ensuring that Cohen’s work is more than just remembered, but spread far and wide and used to tackle the kinds of open problems that he adored.

Those wishing to making contributions in Cohen’s name should consider givedirectly.org, a charity he admired that provides money to poor people in Africa.

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Point of Sale Terminals Market (POS Market) forecast by 2022 published by leading research firm

Emerging technologies increases the demand for the POS (Point of sale) Terminal Market; convenience and flexibility of POS terminals minimized customers waiting time, improved billing process, maintained customer records safely as per security concerns, data back up and pertaining personal information of customer confidential, may inhibit the global POS terminal market.

Digital payment anticipated the POS terminal market growth valued at approximately US$45.97 Bn in 2016 and expected to reach approximately US$98.27 Bn by 2022. Increasing demand for wireless technologies expected to witness growth at 20% of CAGR in between 2017 and 2022.

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POS terminals transmit encrypted tokens during the payment process; its advanced feature includes inventory management, CRM financials and the proliferation of NFC and EMV-enabled devices may drive the industrial market in the next years.

The geographical distribution of the global POS terminals market considered the regional markets of North America, Europe, Asia Pacific, Latin America and rest of the world.

In regional segmentation North America accounted the largest market share of POS terminal followed with Europe and Asia-Pacific respectively. The North America dominated the POS terminal market with the rising adoption of wireless technology across the hospitality applications, restaurants, automotive shops and grocery stores. However the region of Asia-Pacific surprisingly anticipated the POS terminal market with the growing CAGR of 13% in upcoming future. Rapid advancements in the card acceptance and use of debit cards are expected to serve high growth over the forecast period in Asia-Pacific region; especially in India and China; where supermarkets are owing to grow in the upcoming years. It will drive the global revenue of the POS terminals market.

Increasing governmental support in order to improve the digital transaction with advanced technologies boosted the global market of the POS terminals especially in developed economies like Asia-Pacific region. The growing usage of POS terminals with NFC devices in the industrial and retail sector will expected to drive CAGR of 10% over the forecast period. A sustainable governmental effort to promote the computerized payment instead of traditional transaction with cash register will encourage the POS terminal market in this region.

The competitive market for the POS terminals includes New POS technology, NCR Corporation, NFC Corporation, PAX technology, Veri fone Systems, Ingenico SA, Panasonic Corporation, Toshiba Corporation, Cisco Systems and others.

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Application segment of the POS terminals include healthcare, retail, hospitality, entertainment, warehouses, automotive shops, grocery stores and e-commerce sites. The growing usage of POS terminals in these segments witnessed a significant turnaround over the forecast period.

On the basis of component segment POS terminal market segmented into hardware and software, it simplifies the accounting process and promotes the digital payment platform. Card acceptance increases the merchants to enroll the digital transaction will exhibit remarkable opportunities and growth in the POS terminal market.

An advanced and appropriate POS terminal can simplifies the transaction process and save time and money with efficient customer services, it is highly adopted by retailers and e-Commerce companies as per security concerns and confidential financial information of the customers.

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Automotive Lightweight Materials Market is expected to reach US$ 180.9 Bn by 2025, expanding at a CAGR of 13.1% from 2017 to 2025.

According to a new market research report published by Credence Research, Inc. “Automotive Lightweight Materials Market – Growth, Future Prospects and Competitive Analysis, 2017 – 2025,” automotive lightweight material market was valued at US$ 59.7 Bn in 2016, and is expected to reach US$ 180.9 Bn by 2025, expanding at a CAGR of 13.1% from 2017 to 2025.

Market Insights

Lightweight materials help to decrease the weight of the vehicle and reduce energy consumption. Technological advancement, worldwide increase in vehicle production and rise in disposable income are the major factors driving the growth of automotive lightweight material market. Government regulation on environmental and standard enforced to cut down CO2 emission and technological evolution are driving the global automotive lightweight materials market. High cost associated with lightweight materials may restrain the growth of automotive lightweight materials market.

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Browse the full Automotive Lightweight Materials Market – Growth, Future Prospects and Competitive Analysis, 2017 – 2025 report at http://www.credenceresearch.com/report/automotive-lightweight-materials-market

Chassis and suspension comprise more than 30% of the overall weight of the vehicle, which creates the huge market for the lightweight materials. The lightweight materials which is used in chassis and suspension are AHSS and aluminum. The plastic materials segment is likely to grow at the fastest rate in the forecast period due to increased usage of plastic in automobile interiors, such as seats, dashboard, instrument panel, and interior roofs. Electric vehicles uses large amount of lightweight materials, as these are mainly driven by battery, wherein lightweight materials help to improve their performance.

North America and Europe were the largest regional markets for automotive lightweight materials. Advanced fuel economy, growing demand for low CO2 emission and stringent government regulations are supporting the lightweight materials market in the region. Government raised the norms such as CAFÉ fuel standards and EPA Tier-3 norms for light duty vehicles, to ensure that a vehicles produced from now on would be much lighter in weight. North America has the largest market for light trucks. In North America highest demand for automotive lightweight material is majorly driven by U.S. Asia Pacific will be the fastest growing region in the forecast period due to an increase in the production of automobiles followed by rise in the demand for fuel efficient vehicles. In Asia Pacific demand is manly comes from countries like India, China, and Japan.

Some of the major companies operating in the market include Alcoa, Inc., BASF SE, Thyssenkrupp AG, Covestro AG, Arcelormittal S.A., Lyondellbasell Industries N.V., Novelis, Inc., Toray Industries, Inc., PPG Industries, Inc., and Owens Corning.

Browse the full Automotive Lightweight Materials Market – Growth, Future Prospects and Competitive Analysis, 2017 – 2025 report at http://www.credenceresearch.com/report/automotive-lightweight-materials-market

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Bug-repair system learns from example

Anyone who’s downloaded an update to a computer program or phone app knows that most commercial software has bugs and security holes that require regular “patching.”

Often, those bugs are simple oversights. For example, the program tries to read data that have already been deleted. The patches, too, are often simple — such as a single line of code that verifies that a data object still exists.

That simplicity has encouraged computer scientists to explore the possibility of automatic patch generation. Several research groups, including that of Martin Rinard, an MIT professor of electrical engineering and computer science, have developed templates that indicate the general forms that patches tend to take. Algorithms can then use the templates to generate and evaluate a host of candidate patches.

Recently, at the Association for Computing Machinery’s Symposium on the Foundations of Software Engineering, Rinard, his student Fan Long, and Peter Amidon of the University of California at San Diego presented a new system that learns its own templates by analyzing successful patches to real software.

Where a hand-coded patch-generation system might feature five or 10 templates, the new system created 85, which makes it more diverse but also more precise. Its templates are more narrowly tailored to specific types of real-world patches, so it doesn’t generate as many useless candidates. In tests, the new system, dubbed Genesis, repaired nearly twice as many bugs as the best-performing hand-coded template system.

Thinning the herd

“You are navigating a tradeoff,” says Long, an MIT graduate student in electrical engineering and computer science and first author on the paper. “On one hand, you want to generate enough candidates that the set you’re looking through actually contains useful patches. On the other hand, you don’t want the set to include so many candidates that you can’t search through it.”

Every item in the data set on which Genesis was trained includes two blocks of code: the original, buggy code and the patch that repaired it. Genesis begins by constructing pairs of training examples, such that every item in the data set is paired off with every other item.

Genesis then analyzes each pair and creates a generic representation — a draft template — that will enable it to synthesize both patches from both originals. It may synthesize other, useless candidates, too. But the representation has to be general enough that among the candidates are the successful patches.

Next, Genesis tests each of its draft templates on all the examples in the training set. Each of the templates is based on only two examples, but it might work for several others. Each template is scored on two criteria: the number of errors that it can correct and the number of useless candidates it generates. For instance, a template that generates 10 candidates, four of which patch errors in the training data, might score higher than one that generates 1,000 candidates and five correct patches.

On the basis of those scores, Genesis selects the 500 most promising templates. For each of them, it augments the initial two-example training set with each of the other examples in turn, creating a huge set of three-example training sets. For each of those, it then varies the draft template, to produce a still more general template. Then it performs the same evaluation procedure, extracting the 500 most promising templates.

Covering the bases

After four rounds of this process, each of the 500 top-ranking templates has been trained on five examples. The final winnowing uses slightly different evaluation criteria, ensuring that every error in the training set that can be corrected will be. That is, there may be a template among the final 500 that patches only one bug, earning a comparatively low score in the preceding round of evaluation. But if it’s the only template that patches that bug, it will make the final cut.

In the researchers’ experiments, the final winnowing reduced the number of templates from 500 to 85. Genesis works with programs written in the Java programming language, and the MIT researchers compared its performance with that of the best-performing hand-coded Java patch generator. Genesis correctly patched defects in 21 of 49 test cases drawn from 41 open-source programming projects, while the previous system patched 11.

It’s possible that more training data and more computational power — to evaluate more candidate templates — could yield still better results. But a system that allows programmers to spend only half as much time trying to repair bugs in their code would be useful nonetheless.

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“Superhero” robot wears different outfits for different tasks

From butterflies that sprout wings to hermit crabs that switch their shells, many animals must adapt their exterior features in order to survive. While humans don’t undergo that kind of metamorphosis, we often try to create functional objects that are similarly adaptive — including our robots.

Despite what you might have seen in “Transformers” movies, though, today’s robots are still pretty inflexible. Each of their parts usually has a fixed structure and a single defined purpose, making it difficult for them to perform a wide variety of actions.

Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) are aiming to change that with a new shape-shifting robot that’s something of a superhero: It can transform itself with different “outfits” that allow it to perform different tasks.

Dubbed “Primer,” the cube-shaped robot can be controlled via magnets to make it walk, roll, sail, and glide. It carries out these actions by wearing different exoskeletons, which start out as sheets of plastic that fold into specific shapes when heated. After Primer finishes its task, it can shed its “skin” by immersing itself in water, which dissolves the exoskeleton.

“If we want robots to help us do things, it’s not very efficient to have a different one for each task,” says Daniela Rus, CSAIL director and principal investigator on the project. “With this metamorphosis-inspired approach, we can extend the capabilities of a single robot by giving it different ‘accessories’ to use in different situations.”

Primer’s various forms have a range of advantages. For example, “Wheel-bot” has wheels that allow it to move twice as fast as “Walk-bot.” “Boat-bot” can float on water and carry nearly twice its weight. “Glider-bot” can soar across longer distances, which could be useful for deploying robots or switching environments.

Primer can even wear multiple outfits at once, like a Russian nesting doll. It can add one exoskeleton to become “Walk-bot,” and then interface with another, larger exoskeleton that allows it to carry objects and move two body lengths per second. To deploy the second exoskeleton, “Walk-bot” steps onto the sheet, which then blankets the bot with its four self-folding arms.

“Imagine future applications for space exploration, where you could send a single robot with a stack of exoskeletons to Mars,” says postdoc Shuguang Li, one of the co-authors of the study. “The robot could then perform different tasks by wearing different ‘outfits.’”

The project was led by Rus and Shuhei Miyashita, a former CSAIL postdoc who is now director of the Microrobotics Group at the University of York. Their co-authors include Li and graduate student Steven Guitron. An article about the work appears in the journal Science Robotics on Sept. 27.

Robot metamorphosis

Primer builds on several previous projects from Rus’ team, including magnetic blocks that can assemble themselves into different shapes and centimeter-long microrobots that can be precisely customized from sheets of plastic.

While robots that can change their form or function have been developed at larger sizes, it’s generally been difficult to build such structures at much smaller scales.

“This work represents an advance over the authors’ previous work in that they have now demonstrated a scheme that allows for the creation of five different functionalities,” says Eric Diller, a microrobotics expert and assistant professor of mechanical engineering at the University of Toronto, who was not involved in the paper. “Previous work at most shifted between only two functionalities, such as ‘open’ or ‘closed’ shapes.”

The team outlines many potential applications for robots that can perform multiple actions with just a quick costume change. For example, say some equipment needs to be moved across a stream. A single robot with multiple exoskeletons could potentially sail across the stream and then carry objects on the other side.

“Our approach shows that origami-inspired manufacturing allows us to have robotic components that are versatile, accessible, and reusable,” says Rus, the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science at MIT.

Designed in a matter of hours, the exoskeletons fold into shape after being heated for just a few seconds, suggesting a new approach to rapid fabrication of robots.

“I could envision devices like these being used in ‘microfactories’ where prefabricated parts and tools would enable a single microrobot to do many complex tasks on demand,” Diller says.

As a next step, the team plans to explore giving the robots an even wider range of capabilities, from driving through water and burrowing in sand to camouflaging their color. Guitron pictures a future robotics community that shares open-source designs for parts much the way 3-D-printing enthusiasts trade ideas on sites such as Thingiverse.

“I can imagine one day being able to customize robots with different arms and appendages,” says Rus. “Why update a whole robot when you can just update one part of it?”

This project was supported, in part, by the National Science Foundation.

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Capsule Filler Machines Market 2017-2025 by Segmentation Based on Product, Application and Region

According to a new market research report published by Credence Research “Capsule Filler Machines Market (Machine Type – Manual, Semi-automatic, Fully Automatic and Hybrid; Capacity – Small (Upto 50,000 Capsules), Medium (50,000 to 100,000 Capsules) and High (More than 100,000 Capsules)) – Growth, Future Prospects and Competitive Analysis, 2017 – 2025”, the global capsule filler machines market is set to expand with a CAGR of 4.6% through the forecast period of 2017 to 2025.

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Market Insights

Capsule machines are mechanical equipment (manual or automatic) used to fill empty capsules with pharmaceutical or nutritional substances. The filling material may be in the form of powder, liquid or granules. Capsules are among the most popular form of dosage used across medicine and nutrition purposes worldwide. As a result, capsule filler machines have witnessed profound demand as well as advancement, over the period of time. Capsule filling machines are available in both manual as well as automatic modes.

The most prominent factor fueling the demand for capsule filling machines market is the consistently increasing usage of capsules. Capsules are increasingly being favored due to product differentiation, dose flexibility and improved speed-to-market. Thus, in countries where innovative drugs are produced, capsules are primarily preferred due to their distinct advantages over tablets. Similarly, capsules allow easy formulation of different products (e.g. regional medicines) with minimal cost. This is another factor increasing the consumption of capsules. Subsequently, the demand for capsule filler machines is estimated to remain strong in the following years.

Another major factor fueling the capsule filling machines market is the continual advancement in the sector. Manufacturers now provide fully automated capsule filling machines with high output capacity. Machines having output of upto 300,000 capsules per hour are available in the market facilitating high volume production of capsules. Additionally, companies are focused on developing hybrid machines with several additional features including visual inspection, weight inspection and imprinting. This remarkably reduces the manufacturing time of capsules and minimizes the overall costs. All these factors are estimated to contribute to a robust market growth for capsule filling machines during the forecast period.

The global capsule filler machine market is segmented on the basis of technology, applications and geographic regions. Based on the machine type, the market is segmented into manual, semi-automatic, fully automatic and hybrid capsule filler machines. Hybrid machines refer to equipment that are designed with additional features including visual inspection, weight inspection and imprinting. The hybrid capsule filling machines segment is projected to demonstrate the highest growth during the forecast period. The market is segmented, as per the capsule production capacity, into small (upto 50,000 capsules), medium (50,000 to 100,000 capsules) and high (more than 100,000 capsules).

Browse the full report at http://www.credenceresearch.com/report/capsule-filler-machines-market

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