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News Article | May 22, 2017
Site: www.prweb.com

What good is a new piece of fitness equipment if you run out of ideas for using it? ActivMotion Bar’s new 60-day IGNITE™ program provides all the tools for a professional level, at-home functional fitness plan. IGNITE provides the home user with an ActivMotion Bar and access to their 60-day functional program of online videos. This includes 15 workouts ranging from ten to 30 minutes each, training calendar, nutrition tips and a quick start guide. ActivMotion Bars are filled with rolling steel ball bearings that shift gently during movements, producing an unstable and challenging stimulus that promotes enhanced core and total body strength, increased balance, and improved flexibility. The IGNITE workouts are filled with the bends, twists, arcs and paddle movements that were shown to activate muscles up to 173% more than static fitness tools. Prices range from $119.99 to $139.99. In addition to the IGNITE 60-day functional program, ActivMotion Bar also offers a free app for mobile devices with even more short workouts for the home user. And their free monthly newsletter includes a short video with three new moves to try each week. More information may be found at http://www.activmotionbar.com. The rolling steel weight technology inside the hollow ActivMotion Bars has been embraced by top gyms, trainers, physical therapy practices and professional sports teams. Developed by fitness expert Derek Mikulski, C.S.C.S., The American Council on Exercise, Functional Aging Institute, IDEA Health & Fitness Association, National Academy of Sports Medicine, National Council for Certified Personal Trainers, Pilates Method Alliance and Titleist Performance Institute all offer ActivMotion Bar training to their expert members. While the ActivMotion Bars may look like standard weighted bars, the secret is the rolling steel weights inside the hollow bars. Because the rolling weights create “active resistance,” the muscles, especially those of the core, have to work harder to stabilize the entire body. See more here: https://activmotionbar.cinevee.com/ignite-60-day-home-training-program?autostart=1 When deciding to buy a new fitness tool, it’s important to go with what works. Experts using ActivMotion Bars with their clients include Gunnar Peterson, Leslee Bender, Tony Horton, Danny Musico, Pete McCall, M.S., Chuck Wolf, M.S., et al. The Mayo Clinic uses the bars in their physical therapy department. They are used by professional athletes on the P.G.A. Tour, in the N.F.L., M.L.B. and N.H.L. Whether the bars are used in the gym or the home, the results are profound. ActivMotion Bars come in 4 1/2, six, eight, 10, 15, and 18-pound bars. The lightest bar is four feet long. All others are five feet long. For those already owning ActivMotion Bars, the IGNITE workouts may be purchased separately. It costs $24.99 to rent all 15 digital workouts and $59.99 to download and own them all. ActivMotion Bars are the invention of Derek Mikulski, CSCS. A native of Detroit, Michigan, Mikulski holds a Bachelor of Science degree in health education and promotion from Central Michigan University. He also has general and specialized fitness training certifications from N.A.S.M., N.S.C.A. and N.P.T.I. and is a Certified Strength and Conditioning Specialist (C.S.C.S.) through the N.S.C.A. He turned to fitness in high school to address his own weight struggles. The ActivMotion Bar company is based in Detroit, MI. Follow them on Facebook, Google+, Instagram, Twitter and YouTube.


New outpatient orthopedic clinics — home to therapists Eric Williams, PT, DPT, and Charlene Sheamansmith, PT, DPT Physical Rehabilitation Network (PRN) announces the opening of its newest clinics under the RehabAuthority brand. With additions in Star, Idaho, and Cheyenne, Wyoming, RehabAuthority now operates 18 outpatient physical therapy clinics. The facility in Star, Idaho, is co-owned and managed by Eric Williams, PT, DPT. “RehabAuthority is known for talented clinicians and a strong commitment to their patients,” said Williams. “It’s an honor to be part of the rehab family that has helped so many patients improve their lives.” The Star clinic features custom rehabilitation, injury prevention programs and performance enhancement services. “This is a very exciting period for RehabAuthority,” stated Regional Vice President Galen Danielson, PT, DPT, OCS, Cert MDT, CSMT, CSCS. “With our new clinics and inaugural expansion into the Wyoming market, we look forward to serving these communities and growing to meet their needs.” Leading the Cheyenne, WY clinic are Charlene Sheamansmith, PT, DPT, and Stacy Roth, PT, DPT. Both Charlie and Stacy have been active-duty military members and bring a wealth of experience to the new clinic as co-owners and managers. The Cheyenne facility showcases state-of-the-art equipment to augment the high quality of care provided by the team of clinical experts. Visit rehabauthority.com for a comprehensive list of locations and services. Physical Rehabilitation Network, LLC (PRN) is a privately held physical therapy organization based in Carlsbad, California. PRN is prominently recognized as the leading therapist-friendly rehab organization in the western part of the United States through its partnership model with premier physical and occupational therapists. The company currently operates over 100 locations providing local autonomy and branding to its therapist partners while streamlining all traditional overhead activities of running a practice. PRN is actively seeking high-quality, entrepreneurially driven physical and occupational therapists interested in partnering with PRN as the company expands its footprint providing opportunities for therapists to own their own clinic. For more information on PRN services and its model, please contact Michael Rice at 312.560.6020 / mrice@prnpt.com, or visit us at www.prnpt.com.


News Article | May 26, 2017
Site: www.prlog.org

SPORTFIT will be hosting 10 Week Summer Sports Performance and Strength and Conditioning Camps for middle and high school athletes -- SPORTFIT is pleased to announce the details of their Summer Sports Performance Camps to take place in Hillsboro, OR, near the Intel Campus. The camps will improve the strength, speed, agility and explosiveness of high school and middle school athletes, while reducing their injury potential.   Training will delve deeply into the fundamentals of athletic movement and safe resistance training. Each session will begin with soft tissue mobilization followed by a dynamic warm up to prepare the body for movement.  Careful attenion is devoted to instruction in proper movement skills, before progressing through speed and agility training. This is followed with appropriate plyometrics for individual athletes to improve upper body power and jumping ability, and finally strength training.  The high school athletes are also taught proper performance of the olympic lifts to further enhance power and explosiveness.Coaches will include James Cavin MS, PT, CSCS, PES, a Physical Therapist and former Division I collegiate wrestler at Boston University, and Sam Johnson, a strength coach and former pitcher for the University of Oregon and Westview High School, where he won a 3 Metro Leauge Championships and an Oregon State Title.The camps will run for 10 weeks, from June 26-August 25.The camp for High School Athletes will run Mondays, Wednesdays, and Fridays from 1:30 to 3:00 PM; Middle school athletes will train from 3:15 through 4:15 PM on Mondays and Wednesdays.


News Article | March 11, 2016
Site: www.nanotech-now.com

Abstract: All materials are made up of atoms, which vibrate. These vibrations, or 'phonons', are responsible, for example, for how electric charge and heat is transported in materials. Vibrations of metals, semiconductors, and insulators in are well studied; however, now materials are being nanosized to bring better performance to applications such as displays, sensors, batteries, and catalytic membranes. What happens to vibrations when a material is nanosized has until now not been understood. Soft Surfaces Vibrate Strongly In a recent publication in Nature, ETH Professor Vanessa Wood and her colleagues explain what happens to atomic vibrations when materials are nanosized and how this knowledge can be used to systematically engineer nanomaterials for different applications. The paper shows that when materials are made smaller than about 10 to 20 nanometers -- that is, 5,000 times thinner than a human air -- the vibrations of the outermost atomic layers on surface of the nanoparticle are large and play an important role in how this material behaves. "For some applications, like catalysis, thermoelectrics, or superconductivity, these large vibrations may be good, but for other applications like LEDs or solar cells, these vibrations are undesirable," explains Wood. Indeed, the paper explains why nanoparticle-based solar cells have until now not met their full promise. The researchers showed using both experiment and theory that surface vibrations interact with electrons to reduce the photocurrent in solar cells. "Now that we have proven that surface vibrations are important, we can systematically design materials to suppress or enhance these vibrations," say Wood. Improving Solar Cells Wood's research group has worked for a long time on a particular type of nanomaterial -- colloidal nanocrystals -- semiconductors with a diameter of 2 to 10 nanometers. These materials are interesting because their optical and electrical properties are dependent on their size, which can be easily changed during their synthesis. These materials are now used commercially as red- and green-light emitters in LED-based TVs and are being explored as possible materials for low cost, solution-processed solar cells. Researchers have noticed that placing certain atoms around the surface of the nanocrystal can improve the performance of solar cells. The reason why this worked had not been understood. The work published in the Nature paper now gives the answer: a hard shell of atoms can suppress the vibrations and their interaction with electrons. This means a higher photocurrent and a higher efficiency solar cell. Big Science to Study the Nanoscale Experiments were conducted in Professor Wood's labs at ETH Zurich and at the Swiss Spallation Neutron Source at the Paul Scherrer Institute. By observing how neutrons scatter off atoms in a material, it is possible to quantify how atoms in a material vibrate. To understand the neutron measurements, simulations of the atomic vibrations were run at the Swiss National Supercomputing Center (CSCS) in Lugano. Wood says, "without access to these large facilities, this work would not have been possible. We are incredibly fortunate here in Switzerland to have these world class facilities." For more information, please click If you have a comment, please us. Issuers of news releases, not 7th Wave, Inc. or Nanotechnology Now, are solely responsible for the accuracy of the content.


News Article | March 10, 2016
Site: www.cemag.us

All materials are made up of atoms, which vibrate. These vibrations, or "phonons", are responsible, for example, for how electric charge and heat is transported in materials. Vibrations of metals, semiconductors, and insulators in are well studied; however, now materials are being nanosized to bring better performance to applications such as displays, sensors, batteries, and catalytic membranes. What happens to vibrations when a material is nanosized has until now not been understood. In a recent publication in Nature, ETH Zürich Professor Vanessa Wood and her colleagues explain what happens to atomic vibrations when materials are nanosized and how this knowledge can be used to systematically engineer nanomaterials for different applications. The paper shows that when materials are made smaller than about 10 to 20 nanometers — that is, 5,000 times thinner than a human air — the vibrations of the outermost atomic layers on surface of the nanoparticle are large and play an important role in how this material behaves. “For some applications, like catalysis, thermoelectrics, or superconductivity, these large vibrations may be good, but for other applications like LEDs or solar cells, these vibrations are undesirable,” explains Wood. Indeed, the paper explains why nanoparticle-based solar cells have until now not met their full promise. The researchers showed using both experiment and theory that surface vibrations interact with electrons to reduce the photocurrent in solar cells. “Now that we have proven that surface vibrations are important, we can systematically design materials to suppress or enhance these vibrations,” says Wood. Wood’s research group has worked for a long time on a particular type of nanomaterial — colloidal nanocrystals — semiconductors with a diameter of 2 to 10 nanometers. These materials are interesting because their optical and electrical properties are dependent on their size, which can be easily changed during their synthesis. These materials are now used commercially as red- and green-light emitters in LED-based TVs and are being explored as possible materials for low cost, solution-processed solar cells. Researchers have noticed that placing certain atoms around the surface of the nanocrystal can improve the performance of solar cells. The reason why this worked had not been understood. The work published in the Nature paper now gives the answer: a hard shell of atoms can suppress the vibrations and their interaction with electrons. This means a higher photocurrent and a higher efficiency solar cell. Experiments were conducted in Wood’s labs at ETH Zurich and at the Swiss Spallation Neutron Source at the Paul Scherrer Institute. By observing how neutrons scatter off atoms in a material, it is possible to quantify how atoms in a material vibrate. To understand the neutron measurements, simulations of the atomic vibrations were run at the Swiss National Supercomputing Center (CSCS) in Lugano. Wood says, “without access to these large facilities, this work would not have been possible. We are incredibly fortunate here in Switzerland to have these world class facilities.”


News Article | February 1, 2016
Site: www.scientificcomputing.com

Researchers have created the world’s smallest integrated optical switch. Applying a small voltage causes an atom to relocate, turning the switch on or off. The quantity of data exchanged via communications networks around the globe is growing at a breathtaking rate. The volume of data for wired and mobile communications is currently increasing by 23 and 57 percent respectively every year. It is impossible to predict when this growth will end. This also means that all network components must constantly be made more efficient. These components include so-called modulators, which convert the information that is originally available in electrical form into optical signals. Modulators are, therefore, nothing more than fast electrical switches that turn a laser signal on or off at the frequency of the incoming electrical signals. Modulators are installed in data centers in their thousands. However, they all have the disadvantage of being quite large. Measuring a few centimeters across, they take up a great deal of space when used in large numbers. Six months ago, a working group led by Jürg Leuthold, Professor of Photonics and Communications at ETH Zurich, already succeeded in proving that the technology could be made smaller and more energy-efficient. As part of that work, the researchers presented a micromodulator measuring just 10 micrometers across — or 10,000 times smaller than modulators in commercial use (see ETH News). Leuthold and his colleagues have now taken this to the next level by developing the world’s smallest optical modulator. And this is probably as small as it can get: the component operates at the level of individual atoms. The footprint has, therefore, been further reduced by a factor of 1,000 if you include the switch together with the light guides. However, the switch itself is even smaller, with a size measured on the atomic scale. The team’s latest development was recently presented in the journal Nano Letters. In fact, the modulator is significantly smaller than the wavelength of light used in the system. In telecommunications, optical signals are transmitted using laser light with a wavelength of 1.55 micrometers. Normally, an optical device cannot be smaller than the wavelength it should process. “Until recently, even I thought it was impossible for us to undercut this limit,” stresses Leuthold. But his senior scientist Alexandros Emboras proved the laws of optics wrong by successfully reconfiguring the construction of a modulator. This construction made it possible to penetrate the order of magnitude of individual atoms, even though the researchers were using light with a “standard wavelength.” Emboras’s modulator consists of two tiny pads, one made of silver and the other of platinum, on top of an optical waveguide made of silicon. The two pads are arranged alongside each other at a distance of just a few nanometers, with a small bulge on the silver pad protruding into the gap and almost touching the platinum pad. And here’s how the modulator works: light entering from an optical fiber is guided to the entrance of the gap by the optical waveguide. Above the metallic surface, the light turns into a surface plasmon. A plasmon occurs when light transfers energy to electrons in the outermost atomic layer of the metal surface, causing the electrons to oscillate at the frequency of the incident light. These electron oscillations have a far smaller diameter than the ray of light itself. This allows them to enter the gap and pass through the bottleneck. On the other side of the gap, the electron oscillations can be converted back into optical signals. If a voltage is now applied to the silver pad, a single silver atom or, at most, a few silver atoms move towards the tip of the point and position themselves at the end of it. This creates a short circuit between the silver and platinum pads, so that electrical current flows between them. This closes the loophole for the plasmon; the switch flips and the state changes from “on” to “off” or vice versa. As soon as the voltage falls below a certain threshold again, a silver atom moves back. The gap opens, the plasmon flows, and the switch is “on” again. This process can be repeated millions of times. ETH Professor Mathieu Luisier, who participated in this study, simulated the system using a high-performance computer at the Swiss National Supercomputing Centre (CSCS) in Lugano. This allowed him to confirm that the short circuit at the tip of the silver point is brought about by a single atom. As the plasmon has no other options than to pass through the bottleneck either completely or not at all, this produces a truly digital signal — a one or a zero. “This allows us to create a digital switch, as with a transistor. We have been looking for a solution like this for a long time,” summarizes Leuthold. As yet, the modulator is not ready for series production. Although it has the advantage of operating at room temperature, unlike other devices that work using quantum effects at this order of magnitude, it still remains very slow for a modulator: so far, it only works for switching frequencies in the megahertz range or below. The ETH researchers want to fine-tune it for frequencies in the gigahertz to terahertz range. The researchers also want to further improve the lithography method, which was redeveloped by Emboras from scratch to build the parts, so that components like this can be produced reliably in future. At present, fabrication is only successful in one out of every six attempts. Nevertheless, the researchers consider this a success, as lithography processes on the atomic scale remain uncharted territory. In order to continue his research into the nanomodulator, Leuthold has strengthened his team. However, he points out that greater resources would be required to develop a commercially available solution. Despite this, the ETH professor is confident that he and his team will be able to present a practicable solution within the next few years. Citation: A. Emboras, J. Niegemann, P. Ma, C. Haffner, A. Pedersen, M. Luisier, C. Hafner, T. Schimmel, and J. Leuthold, Atomic Scale Plasmonic Switch, Nano Letters 16, 709-714 (2016). DOI: 10.1021/acs.nanolett.5b04537


News Article | December 7, 2016
Site: www.techrepublic.com

The latest collaboration between Microsoft and Cray could dramatically lessen the time it takes data scientists to train and run data models that play into deep learning technologies. On Wednesday, at the 2016 Neural Information Processing Systems (NIPS) Conference in Spain, the two companies showed off their latest supercomputing work in broadening the usefulness and scale of deep learning algorithms. According to a press release announcing the combined work, the premise for the partnership came from the idea that conventional systems and architectures in deep learning take too long to train, and thus limit what can be accomplished with them. To address the challenge, Microsoft and Cray teamed up, alongside the Swiss National Supercomputing Centre (CSCS), to explore how they could use supercomputing to expand deep learning. The result is that the Microsoft Cognitive Toolkit was scaled to work on a Cray XC50 supercomputer, nicknamed "Piz Daint," that resides at the at CSCS. SEE: IBM, NVIDIA partner for 'fastest deep learning enterprise solution' in the world The end result is that the time it takes to get actual results from deep learning algorithms is shortened dramatically. According to the release, the combined efforts can get results to data scientists in minutes or hours instead of weeks or months. "With the introduction of supercomputing architectures and technologies to deep learning frameworks, customers now have the ability to solve a whole new class of problems, such as moving from image recognition to video recognition, and from simple speech recognition to natural language processing with context," the release stated. The reason this seems to work is because deep learning problems share similarities, on an algorithmic level, with some of the applications that are typically reserved for supercomputers like the Cray XC50. And, because of the increased compute resources available to the deep learning models, they are able to be trained at a much more rapid pace. "What is most exciting is that our researchers and scientists will now be able to use our existing Cray XC supercomputer to take on a new class of deep learning problems that were previously infeasible," Thomas C. Schulthess, director of the CSCS, said in the press release. The Cray supercomputer on which the Microsoft Cognitive Toolkit was scaled to run had 1,000 NVIDIA Tesla P100 GPU accelerators. In addition to speeding up traditional deep learning processes, the collaboration also opens up options for more complex and in-depth deep learning workloads in the future, the release said. In order to further support deep learning in supercomputing, Cray is supporting customers of its Cray XC series with deep learning toolkits, like the Microsoft Cognitive Toolkit that was used in this collaboration. "We are working to unlock possibilities around new approaches and model sizes, turning the dreams and theories of scientists into something real that they can explore." Mark S. Staveley, Cray's director of deep learning and machine learning, said in the press release. In August, similar work began taking place at nonprofit artificial intelligence research company OpenAI. The company, backed by Elon Musk, became the first customer of the Nvidia DGX-1, which is billed as the "world's first deep learning supercomputer in a box," and could help accelerate Open AI's research.


News Article | February 2, 2016
Site: www.nanotech-now.com

Abstract: The quantity of data exchanged via communications networks around the globe is growing at a breathtaking rate. The volume of data for wired and mobile communications is currently increasing by 23% and 57% respectively every year. It is impossible to predict when this growth will end. This also means that all network components must constantly be made more efficient. These components include so-called modulators, which convert the information that is originally available in electrical form into optical signals. Modulators are therefore nothing more than fast electrical switches that turn a laser signal on or off at the frequency of the incoming electrical signals. Modulators are installed in data centres in their thousands. However, they all have the disadvantage of being quite large. Measuring a few centimetres across, they take up a great deal of space when used in large numbers. From micromodulators to nanomodulators Six months ago, a working group led by Jürg Leuthold, Professor of Photonics and Communications already succeeded in proving that the technology could be made smaller and more energy-efficient. As part of that work, the researchers presented a micromodulator measuring just 10 micrometres across - or 10,000 times smaller than modulators in commercial use. Leuthold and his colleagues have now taken this to the next level by developing the world's smallest optical modulator. And this is probably as small as it can get: the component operates at the level of individual atoms. The footprint has therefore been further reduced by a factor of 1,000 if you include the switch together with the light guides. However, the switch itself is even smaller, with a size measured on the atomic scale. The team's latest development was recently presented in the journal Nano Letters. In fact, the modulator is significantly smaller than the wavelength of light used in the system. In telecommunications, optical signals are transmitted using laser light with a wavelength of 1.55 micrometres. Normally, an optical device can not be smaller than the wavelength it should process. "Until recently, even I thought it was impossible for us to undercut this limit," stresses Leuthold. New structure But his senior scientist Alexandros Emboras proved the laws of optics wrong by successfully reconfiguring the construction of a modulator. This construction made it possible to penetrate the order of magnitude of individual atoms, even though the researchers were using light with a "standard wavelength". Emboras's modulator consists of two tiny pads, one made of silver and the other of platinum, on top of an optical waveguide made of silicon. The two pads are arranged alongside each other at a distance of just a few nanometres, with a small bulge on the silver pad protruding into the gap and almost touching the platinum pad. Short circuit thanks to a silver atom And here's how the modulator works: light entering from an optical fibre is guided to the entrance of the gap by the optical waveguide. Above the metallic surface, the light turns into a surface plasmon. A plasmon occurs when light transfers energy to electrons in the outermost atomic layer of the metal surface, causing the electrons to oscillate at the frequency of the incident light. These electron oscillations have a far smaller diameter than the ray of light itself. This allows them to enter the gap and pass through the bottleneck. On the other side of the gap, the electron oscillations can be converted back into optical signals. If a voltage is now applied to the silver pad, a single silver atom or, at most, a few silver atoms move towards the tip of the point and position themselves at the end of it. This creates a short circuit between the silver and platinum pads, so that electrical current flows between them. This closes the loophole for the plasmon; the switch flips and the state changes from "on" to "off" or vice versa. As soon as the voltage falls below a certain threshold again, a silver atom moves back. The gap opens, the plasmon flows, and the switch is "on" again. This process can be repeated millions of times. ETH Professor Mathieu Luisier, who participated in this study, simulated the system using a high-performance computer at the CSCS in Lugano. This allowed him to confirm that the short circuit at the tip of the silver point is brought about by a single atom. A truly digital signal As the plasmon has no other options than to pass through the bottleneck either completely or not at all, this produces a truly digital signal - a one or a zero. "This allows us to create a digital switch, as with a transistor. We have been looking for a solution like this for a long time," summarises Leuthold. As yet, the modulator is not ready for series production. Although it has the advantage of operating at room temperature, unlike other devices that work using quantum effects at this order of magnitude, it still remains very slow for a modulator: so far, it only works for switching frequencies in the megahertz range or below. The ETH researchers want to fine-tune it for frequencies in the gigahertz to terahertz range. Improving the lithography process The researchers also want to further improve the lithography method, which was redeveloped by Emboras from scratch to build the parts, so that components like this can be produced reliably in future. At present, fabrication is only successful in one out of every six attempts. Nevertheless, the researchers consider this a success, as lithography processes on the atomic scale remain uncharted territory. In order to continue his research into the nanomodulator, Leuthold has strengthened his team. However, he points out that greater resources would be required to develop a commercially available solution. Despite this, the ETH professor is confident that he and his team will be able to present a practicable solution within the next few years. For more information, please click If you have a comment, please us. Issuers of news releases, not 7th Wave, Inc. or Nanotechnology Now, are solely responsible for the accuracy of the content.


PURCHASE, NY--(Marketwired - Feb 28, 2017) - A new study published in Journal of the International Society of Sports Nutrition shows the combination of amylopectin and chromium in Nutrition 21's patented ingredient Velositol doubles the muscle protein synthesis (MPS) rate compared to what was seen when using whey protein alone. Velositol increased MPS by 48 percent from baseline when combined with whey protein (6 grams), as compared to a 24 percent increase seen with whey protein alone. The significant increase in MPS, along with a non-significant increase in insulin to help initiate muscle growth, was noted in the study subjects made up of healthy men and women. Blood glucose levels remained in the healthy, normal range. "This study shows Velositol has the ability to unlock the potential of protein, promote leaner body composition and enhance muscle building," said Joe Weiss, president of Nutrition 21. "This study confirmed our theories, and exceeded our expectations for Velositol." The randomized, double-blind, single-dose, active-controlled crossover study was conducted at The Center for Applied Health Sciences in Stow, Ohio, on 10 healthy men and women ages 22-34. On two different occasions, participants were given a single dose of Velositol with 6 grams of whey protein or 6 grams of whey protein alone, and completed eight sets of bilateral isotonic leg extensions at a load equivalent to 80 percent of their estimated one-repetition maximum. The study was done over an eight-hour time period in which three muscle biopsies were taken at hours 2, 4 and 8 to measure muscle protein synthesis. "Muscle biopsy studies are tightly controlled and highly invasive, so small sample sizes are very common. With a study like this, if you cannot show a difference with 10 people, it's unlikely one exists in the 'real world,'" said Tim N. Ziegenfuss, Ph.D., CSCS, FISSN, lead author of the study and CEO of Center for Applied Health Sciences. "The study results are impressive. It's not only statistically significant that Velositol doubled muscle protein synthesis, but also practically relevant for anyone who is active and may not be consuming enough protein to support enhanced muscle growth. Until this study was done, one of the only ways known to improve the anabolic response to resistance training was to consume more protein, which is not always practical. If future studies confirm our results, Velositol could be a huge benefit not only to people in their 20s and 30s, but especially those in their 40s and 50s and older whose muscles become more resistant to the anabolic effects of protein." Given the success of this study, Nutrition 21 plans to fund more studies on Velositol to further demonstrate the additional benefits Velositol can provide. Currently a pre-clinical study is in progress to show how Velositol affects higher doses of whey protein as well as different types of protein including, pea protein and branch chain amino acids. Velositol was recently named a finalist and nominated for New Hope's NutrAward to be awarded at Natural Products Expo West on March 9, 2017. Expo West attendees may vote at: http://pages.newhope.com/NutrAwards-2017-Voting. For more information on Velositol, visit: http://nutrition21.com. Nutrition 21, a wholly owned subsidiary of JDS Therapeutics, is a leader in the nutritional supplement industry. With many years of biotechnology and pharmaceutical experience, the company's scientific platform has created unique, patented products that are safe and clinically effective. Rigorous preclinical and clinical trials are a key part of its product development strategy to ensure product safety and consumer trust. Nutrition 21 currently holds more than 100 domestic and international issued and pending patents for products. Many support unique claims associated with, among others, glucose metabolism, weight management, cognition and sports nutrition. The company is a developer and marketer of efficacious, high-value, clinically substantiated ingredients for dietary supplements, medical foods and beverages. Nutrition 21's branded ingredients include: Velositol® amylopectin chromium complex, clinically shown to double the effects of whey protein -- significantly increasing muscle protein synthesis, the key to muscle growth; Chromax® chromium picolinate, with clinically substantiated benefits for glucose metabolism, weight management, and brain health; Nitrosigine® bonded arginine silicate is clinically shown to significantly boost nitric oxide levels supporting mental acuity/focus and sports nutrition. Nitric oxide is a key factor in promoting the relaxation of smooth muscle in blood vessels, increasing blood flow to working muscles. For more information, please visit: www.Nutrition21.com


Modelling of crystal fractionation in magmas predicts that the content of compatible trace elements such as strontium (highly enriched in plagioclase, the dominant mineral phase in the mid to upper continental crust) drops in the residual melt and should correlate with the SiO content4. In geochemical datasets, such as the North American Volcanic and Intrusive Rock Database (NAVDAT; http://www.navdat.org), the distribution of strontium for a given SiO range between volcanic and plutonic suites presents a striking conundrum. For dacitic/granodioritic compositions (intermediate SiO content), the frequency of rock samples with similar strontium contents is nearly identical between volcanic and plutonic rocks; for high-SiO magmas, there is a clear trend towards many more low-strontium compositions in volcanic units than in plutonic units. Clearly, geochemical datasets such as NAVDAT may carry sampling biases, but we argue that the number of samples considered (1,989 volcanic rock samples with 65–69% SiO ; 2,355 volcanic rock samples with 73–77% SiO ; 2,018 plutonic rock samples with 65–69% SiO ; and 1,647 plutonic rock samples with 73–77% SiO ; see Fig. 4a) and the prominence of the low-strontium mode in high-SiO rhyolites imply that magmas depleted in strontium are more commonly represented in the eruptive than in the intrusive record. We assume that these low-strontium magmas are formed by interstitial/residual melt extraction from dacitic crystal-rich mushes, and segregate into liquid-dominated caps15, 16, 33, 34 that are consequently more prone to erupt than to stall in the crust. Estimates of volatile mass balance in magmas stored in the crust are generally based on the volatile content dissolved in melt inclusions35. However, melt inclusion data are limited by several factors, including: (1) leakage of volatiles (loss through volume diffusion, cracks or cleavage surfaces); and (2) an inability to record volatiles trapped in hidden reservoirs (exsolved bubbles or sulfide phases). The excess sulfur paradox is a clear consequence of such limitations. Sulfur degassing from the melt during magma ascent in the conduit does not contribute to the excess sulfur because it is typically accounted for in the petrologic estimate from melt inclusions2. The processes that govern the unbalanced sulfur budget are the build-up of an abundant sulfur-rich MVP produced by crystallization-driven exsolution, the transport and accumulation of sulfur-rich MVP from deeper untapped portions of the magmatic system, and, in some cases, the breakdown of sulfides or anhydrite before an eruption1, 2, 36, 37. In the context of the large excesses of sulfur released during the explosive eruption of crystal-poor rhyolitic caps, the contributions to the total sulfur mass budget from crystallization-driven exsolution and sulfide/anhydrite breakdown are bound to be tenuous, and call for an efficient migration and accumulation of MVP exsolved deeper down (by second boiling in the crystal-rich mushy roots of the magmatic system; see Fig. 4b). At high crystallinity, buoyant bubbles are likely to deform along the direction perpendicular to gravity and, therefore, experience a significant hydrostatic pressure drop. Once this pressure drop is high enough to invade a pore throat, drainage is initiated and the blobs of MVP migrate vertically. The formation of anisotropic MVP clusters along the direction of gravity requires a confinement from the crystal phases to work against interfacial tension. Interfacial tension will tend to make bubbles spherical, whereas gravity will provoke the horizontal expansion of bubbles when their ascent is obstructed. Crystal confinement is therefore key to the development and stability of mobile MVP fingers in a crystal mush. In Extended Data Fig. 2, we show snapshots (Extended Data Fig. 2a–c show initial conditions and Extended Data Fig. 2d–f show the steady-state MVP distribution) for three numerical calculations conducted using a multiphase lattice Boltzmann model (that is, the interparticle potential Shan–Chen method21, 38, 39, 40). We implemented this model using the open-source Palabos library (http://www.palabos.org) and ran the simulations on the supercomputer clusters at Georgia Tech, the Swiss Federal Institute of Technology Zurich (ETHZ) and CSCS-Switzerland (the lattice Boltzmann method and code validations are described in detail below). In these calculations, the pore volume fraction of MVP and the size of pore throats are identical but with different crystallinities (crystallinity (1–ϕ) increases to the right). We see that increasing the spatial confinement (crystallinity) leads to enhanced coalescence and the formation of stable fingering. The run at highest crystallinity (Extended Data Fig. 2c, f) maximizes the vertical bubble pressure drop and is the only one that leads to the formation of a continuous fingering feature across the domain. In the other calculations, bubbles are mechanically trapped by capillary and viscous forces. A high MVP volume fraction and high crystallinity favour the formation and stability of viscous fingers, because they prevent the growth of Rayleigh–Plateau instabilities41, 42, 43 that are responsible for the break-up of fingering. In essence, fingering pathways, once established, require little displacement of the viscous melt in the porous medium and reduce therefore the rate of energy dissipation in the melt. This results in an increase of MVP discharge in the mush. In Extended Data Fig. 2g, we report the results of a set of calculations (78 in total) conducted with the same porous medium geometry (porosity 0.4) but a varying initial spatial distribution and volume fraction of MVP. The porous medium is made up of spherical pores, each connected to six cylindrical throats along each dimension (in three dimensions). Throat radii are randomly generated to introduce a random distribution of capillary entry pressure for the MVP invasion in neighbour pores. The calculations at a given MVP pore volume fraction are repeated with a different initial distribution of MVP in the pore space. These calculations clearly show that the MVP discharge through the porous medium increases with the MVP pore volume fraction. At low MVP volume fraction (red region), MVP remains distributed as discrete bubbles trapped in the medium because of capillary and viscous forces. The discharge is negligible. At intermediate MVP pore volume fraction (green region), coalescence becomes important and makes the formation of percolating fingering pathways of MVP possible, which leads to a sharp increase in MVP discharge. However, in this region, the connectivity of fingering pathways depends on the initial distribution of MVP. In this regime, the runs that do not yield an efficient MVP discharge often display intermittent formation and destruction of fingering pathways, leading to successive periods of short-lived efficient transport and periods of capillary and viscous trapping of MVP bubbles. Above a certain pore volume fraction (blue region), the MVP always forms and sustains percolating fingering pathways and the MVP migration rate is fast. The rising velocity of an isolated bubble through an infinite stagnant fluid can be described by the law derived by Hadamard and Rybczynski (reviewed in refs 44 and 45). However, when it comes to finding the velocity of a single bubble rising inside a cloud of bubbles, the dynamics becomes more complex because bubbles interact hydrodynamically with each other and with the ambient melt. For example, at low Reynolds number, the rising velocity of a trailing bubble aligned with another (lead) bubble along their direction of motion is greater than that of an individual bubble (the Smoluchowski effect; see ref. 46), while misaligned bubbles experience a greater viscous drag because of the melt return flow. Recently, Faroughi and Huber18 characterized both local and non-local bubble interactions theoretically, and proposed a new hindrance function, F(Ψ,λ), which represents the ratio of the migration velocity of a bubble in a suspension to that of the same bubble in a bubble-free melt. The relative velocity of bubbles in a suspension at low Reynolds number is controlled by the balance between buoyancy and viscous stresses. The presence of bubbles decreases the hydrostatic pressure by a factor (1−Ψ), whereas the presence of a cloud of MVP bubbles dispersed in the melt affects the effective shear viscosity of the magma17. The general expression for the hindrance function is18: where represents the drag caused by the return flow of melt, parameterized as: Ψ and Ψ are, respectively, the bubble volume fraction and the random close packing limit for spherical bubbles; β = 0.45, being a geometrical proportionality constant determined experimentally17; captures Smoluchowski’s effect: and expresses the change in momentum diffusivity via: Finally, under the assumption that bubbles are inviscid relative to the melt, we obtain the relative bubble velocity: where U and U are, respectively, the bubble velocity in the suspension and its Stokes ascent velocity. Equation (1) is plotted against experimental data over a wide range of particle volume fractions in Extended Data Fig. 1. We carried out experimental studies of bubble migration by using water injected at the top of a tank filled with silicon oil (Extended Data Fig. 3). The localized and fixed injection points at the top of the tank (water is denser than silicon oils, so buoyancy is reversed compared with the typical situation in a magma reservoir) mimic the localized point sources that will transfer the MVP from the mush to the cap. The experimental set-up allows local bubble plumes to form, where hydrodynamic interactions introduce a smaller penalty to bubble buoyant migration. It is expected that bubble plumes (‘vents’) will form out of the mush in heterogeneous magma bodies; it was therefore necessary to validate equation (1) against this set of experimental data for our MVP cap suspension model (see Extended Data Fig. 1 inset). Note the significant decrease in MVP flux as the bubble fraction increases in a suspension; this contrasts strongly with the results shown in the section ‘MVP migration in the crystal-rich mush’, where the MVP flux increases significantly with increasing volume fraction in a porous mush. Crystal-poor caps are prone to convect, especially when buoyant bubbles are fluxed in from below. Convective motion will affect the migration of buoyant bubbles47. At low Reynolds numbers, the overall motion of bubbles can be decomposed as a vectorial sum between the imposed convective motion and the buoyant phase separation calculated above. The behaviour of bubbles is determined by the ratio of these two velocity components (sometimes parameterized as a Stokes number47). For small (millimetre-size) bubbles in a silicic magma, one can assume that bubbles remain highly coupled to the convective flow motion, except when the flow decelerates in boundary layers next to the edges of the reservoir. Thus, we adapt the model derived by Martin and Nokes48 and also used by Dufek and Bachmann34 for crystal suspensions to calculate the residence time of bubbles in the convecting cap. The main differences between our calculations and those presented in refs 34 and 48 are: (1) in our calculations, the segregating phase comprises buoyant bubbles with free-slip conditions at the interface between bubbles and melt; and (2) we use the hindrance function derived above to correct for the presence of other bubbles, which can significantly affect the buoyant bubbles’ ability to migrate in magmas. The model we obtain for the mass (here volume) conservation of bubbles in the cap therefore reads: where F(Ψ,λ) is the hindrance function calculated from equation (1), H is the thickness of the crystal-poor layer, and q is the volumetric flux of MVP coming from the mush. We first solve equation (2) with q = 0, and retrieve a characteristic residence time for bubbles in a convecting magma. In Extended Data Fig. 4, we show the solution to this differential equation under magmatic conditions. We find that increasing the initial volume fraction of bubbles in a convecting magma has a positive impact on accumulation—that is, at a higher volume fraction, bubbles remain trapped in the convective motion longer because of the hindrance to phase separation. Moreover, the decay rate of the bubble fraction that remains suspended in the convecting magma no longer follows an exponential law18, 48, because of the nonlinear dependence of the MVP ascent velocity on the MVP volume fraction. We also calculate the residence time of bubbles with two arbitrary sizes over a wide range of dynamic shear viscosities of the melt, for dilute (Ψ = 0.01) and high (Ψ = 0.3) volume fractions (Extended Data Fig. 5a). We determine the residence time as the half-life of bubbles in the cap, Ψ(t ) = 0.5Ψ (see ref. 19). where Q = q/U is a dimensionless sourcing term. We solve this equation to find the volume fraction of bubbles that can accumulate in the convecting layer, Ψ . The equation is nonlinear because of the hindrance function, and can admit more than one root. The physically meaningful solution is plotted in Extended Data Fig. 5b, and shows that the accumulated MVP volume fraction increases monotonously with the influx of MVP from the mush. Interestingly, equation (3) does not admit a real solution for injection rates that are greater than 15% of the Stokes final velocity of a 2-mm-diameter bubble in an infinite pool of melt with a dynamic viscosity of 106 Pa s (Extended Data Fig. 5b). Because these injection rates are quite modest, we expect that accumulation of bubbles up to a few tens of per cent in crystal-poor layers in magma chambers is possible. At higher injection rates, accumulation is still possible and likely to occur. However, the lack of a steady solution to our simple convecting suspension model implies that the multiphase dynamics will probably depart from that of a convecting suspension. We hypothesize that, as the volume fraction of bubbles in the crystal-poor cap increases, more complex processes may arise and lead, for example, to massive Rayleigh–Taylor overturns47. We explain the accumulation of MVP in crystal-poor horizons of magma reservoirs by the formation of continuous MVP fingers in crystal-rich environments21, 40 and their break-up at the crystallinity transition between crystal-rich and crystal-poor magmas. This break-up of MVP fingers results in a significant change in the viscous dissipation regime. We investigate this scenario numerically using a rather simplified geometry. We model the complex geometry of the crystal mush at the pore scale as a capillary tube that opens in a crystal-free/solid-free environment (Extended Data Fig. 6a, b). This is a simple proxy for the more realistic mush–cap transition, but it captures its essential ingredients: the dynamics of two immiscible fluids through a change in spatial confinement, where the low viscosity fluid is non-wetting and buoyant. We justify this approximation with the finding21 that the transport of immiscible fluids in a porous medium becomes mostly similar to an annular flow once the percolating pathway for the non-wetting fluid is reached. In our numerical calculations, a constant influx of MVP and a fixed pressure for the melt are set at the bottom boundary (inlet), while the top boundary (outlet) absorbs the outfluxing MVP and maintains a fixed pressure for the melt. The sides are periodic boundaries. The competition between viscous, buoyancy, capillary and inertial forces controls both MVP transport and the breaking of continuous MVP fingering at the crystalline transition between crystal-rich and crystal-poor environments (bubble pinch-off frequency and volume49, 50, 51). Because this balance operates at the pore scale, we resort to pore-scale multiphase flow calculations to study the formation and destruction of fingering pathways in a heterogeneous medium. The force balance can be described with three dimensionless numbers, the Archimedes (Ar), Bond (Bo) and Reynolds (Re) numbers. Ar, Bo and Re represent, respectively, the ratio between buoyancy and viscous forces (equation (4)), the ratio between buoyancy and capillary forces (equation (5)) and the ratio between inertia and viscous forces (equation (6)): where Δρ = ρ − ρ (ρ and ρ are the densities of MVP and melt), g is the acceleration due to gravity, μ the dynamic viscosity of the melt, D the bubble diameter and u the MVP average pore velocity. A rough estimate of these dimensionless numbers in shallow and highly evolved magmatic systems leads to Ar ≪ 1, Re ≪ 1 and Bo ≈ 0.1–1, we obtain a Bo of the order of approximately 0.1 and we force Re and Ar to be lower than unity. Therefore, our results can serve as good first-order estimates for MVP accumulation in crystal-poor environments. The numerical method described in the ‘Lattice Boltzmann for two-phase fluid flows’ section limits us to relatively small viscosity contrasts compared with those expected in magmatic systems. Once pathways of MVP are established in the mush, the melt plays a passive role and does not affect the ascent of the MVP. The same is not true for the suspension, where the viscosity of the melt controls the rate of energy dissipation; as such, we expect accumulation to become more efficient as the viscosity contrast between the wetting and the less viscous non-wetting fluid increases. We decided to use our numerical model to test whether bubbles are likely to accumulate under less optimal conditions, that is, when the viscosity contrast is 1/20 ≤ λ ≤ 1. We found that bubbles accumulate in the crystal-poor region even when the two fluids share the same viscosity (λ = 1), and that the accumulation potential increases as the viscosity contrast becomes more pronounced (Fig. 3). The lattice Boltzmann method (LBM) solves a discretized version of the continuum Boltzmann equation52, 53. Based on statistical mechanics, the LBM focuses on the mechanical interaction of an ensemble average distribution of particles f (x,t), and retrieves mass and momentum conservation (Navier–Stokes) equations from the statistical moment of the Boltzmann equation. The LBM has been extended to multicomponent (MC) immiscible fluid flows. Among others, the MC Shan–Chen (SC) model38, 54 is often applied because of: (1) its straightforward implementation; and (2) the numerical stability of the algorithm in complex geometries such as porous media. In this work, we use the SC model extended by ref. 39, which allows us to model immiscible fluids characterized by notable viscosity contrast. These improvements result from an explicit formulation of the forcing term acting on the particle distribution functions and the use of a multi-relaxation-time (MRT) collision procedure. Below, we describe the improved algorithm briefly; for more details, see refs 39 and 55. The explicit evolution rule for the particle distribution function f α(x,t) with a single-relaxation-time (SRT) collision operator, Ω α, can be written as: where τ is the relaxation time for fluid A and B (α = A,B) and relates to the fluids viscosity; f eq,α is the equilibrium distribution function; and f F,α is the explicit forcing term56. The left-hand side of equation (7) is generally referred to as the streaming of f α values from the lattice node x to one of its neighbours x+e ; the right-hand side (the collision operator Ω α) describes the exchange of momentum between the colliding f values. In equation (7), e are a set of velocity vectors connecting nearest neighbour nodes (the spatial discretization of the lattice). Here we use the D3Q19 lattice—a three-dimensional lattice in which each node is connected to 19 neighbours. Lattice velocities e and weights w for a D3Q19 lattice can be found in ref. 57. The equilibrium distribution function and the explicit forcing term in equation (7) read respectively: Here, c is the lattice speed of sound and ueq is the fluid mixture velocity defined as: where ω  = 1/τ and the statistical moments ρ (density) and ρ u (momentum) are calculated respectively as: The forcing vectors F contain several contributions, notably cohesion (particle–particle), adhesion (particle–wall) and bulk (for example, gravity and buoyancy) forces. The cohesion forces, responsible for the physical separation between immiscible components, are calculated as: where α and β are the two complementary phases and Gc is a free parameter that is used to tune the interfacial tension between the two fluids. The magnitude of the repulsive force applied by fluid B on fluid A at the node x (and vice versa) depends on the density gradient of fluid B (for example, ). The evaluation of is critical for the stability of the calculations. High-density gradients (thin fluid–fluid interfaces) require an extended neighbourhood to reach the required accuracy58. However, a better evaluation of density gradients comes at the price of an increase in computational time (especially in three dimensions). See refs 55, 59 for a detailed description of how to include adhesive and bulk forces. Here, in order to keep the numerical performance acceptable, we calculate the density gradients using the nearest neighbours only. In order to improve the stability and accuracy of the SRT SC algorithm described above, we use an MRT collision operator, Ω MRT. Then, the linear collision operator is re-cast into the space of velocity moments m = M × f = (m , m , m … m , m ) (where M is the transformation matrix57); next, the relaxation parameter of each moment is adjusted individually to improve numerical stability. Ω MRT can be written as: In this equation, Sα are diagonal matrices where the 19 diagonal components represent the relaxation parameter for each moments of f α. As suggested in ref. 57, we use: The 19 components of the vectors mα, meq,α and meF,α can be calculated respectively as: The stability of the algorithm depends mainly on the choice of repulsion constant (Gc) and its correspondent value at solid wall nodes (Gwall, used to introduce wetting forces). Here we want to deal with a highly non-wetting MVP phase. The non-wetting behaviour of MVP affects its dynamics both in the porous medium (higher capillary entry pressures) and at the transition between crystal-rich and crystal-poor environments (pinch-off dynamics). In order to validate the MRT SC multicomponent algorithm that we use to model the capillary finger formation and the pinch-off dynamics (Figs. 2 and 3), we test our model with two benchmarks. The first test is an annular Poiseuille flow, where the non-wetting fluid A is located in the centre of the pipe such that r < R , and the wetting fluid B is placed in the outer ring such that R ≤ r ≤ R (where R is the radius of the pipe flow). Both fluids are accelerated by the same bulk force Fb. For the case of the two-phase Poiseuille profile problem, an analytical solution exists: where ν is the kinematic viscosity of either fluid. In Extended Data Fig. 7a–c, we compare the analytical and numerical solutions for three different viscosity ratios (λ = 1/5, 1/10, or 1/20). The second validation test is a three-dimensional calculation of the equilibrium shape of a drop of fluid A embedded in fluid B and in contact with a flat solid surface. The goal of this validation is to reproduce the correct equilibrium (static) contact angle between the fluids and solid phases for different wetting properties (Extended Data Fig. 7d–f).

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