Please help contribute to the Reddit categorization project here

    mvea

    + friends - friends
    17,004,886 link karma
    200,822 comment karma
    send message redditor for

    [–] Snoring is harmless. Five hours of sleep is enough. Alcohol before bed helps. These are all sleep myths debunked as false in a new study published in the National Sleep Foundation's journal Sleep Health. mvea 1 points ago in Health

    The title of the post is a copy and paste from the first paragraph of the linked popular news article here:

    Snoring is harmless. Five hours of sleep is enough. Alcohol before bed helps. These are all sleep myths debunked as false in a peer-reviewed study published Tuesday in National Sleep Foundation's journal Sleep Health.

    Journal Reference:

    Sleep myths: an expert-led study to identify false beliefs about sleep that impinge upon population sleep health practices

    Rebecca Robbins, PhDa,low asterisk,correspondenceEmail the author PhD Rebecca Robbins, Michael A. Grandner, PhDb, Orfeu M. Buxton, PhDc,j,k,l, Lauren Hale, PhDd, Daniel J. Buysse, MDe, Kristen L. Knutson, PhDf, Sanjay R. Patel, MDg, Wendy M. Troxel, PhDh, Shawn D. Youngstedt, PhDi, Charles A. Czeisler, PhD, MD, FRCPj,k, Girardin Jean-Louis, PhDa

    Sleep Health

    Published Online: April 16, 2019

    Link: https://www.sleephealthjournal.org/#/article/S2352-7218(19)30025-7/fulltext

    Doi: https://doi.org/10.1016/j.sleh.2019.02.002

    Abstract

    Introduction

    False beliefs about sleep can persist despite contradicting scientific evidence, potentially impairing population health. Identifying commonly held false beliefs lacking an evidence base (“myths”) can inform efforts to promote population sleep health.

    Method

    We compiled a list of potential myths using Internet searches of popular press and scientific literature. We used a Delphi process with sleep experts (n = 10) from the fields of sleep medicine and research. Selection and refinement of myths by sleep experts proceeded in 3 phases, including focus groups (Phase 1); email-based feedback to edit, add, or remove myths (Phase 2); and closed-ended questionnaires (Phase 3) where experts rated myths on 2 dimensions, falseness and public health significance, using 5-point Likert scale from 1 (“not at all”) to 5 (“extremely false”).

    Results

    The current study identified 20 sleep myths. Mean expert ratings of falseness ranged from 5.00 (SD = 0.00) for the statement “during sleep the brain is not active” to 2.50 (SD = 1.07) for the statement “sleeping in during the weekends is a good way to ensure you get adequate sleep.” Mean responses to public health significance ranged from 4.63 (SD = 0.74) for debunking the statement that “many adults need only 5 or less hours of sleep for general health” to 1.71 (SD = 0.49) for the statement that “remembering your dreams is a sign of a good night's sleep.”

    Conclusion

    The current study identified commonly held sleep myths that have a limited or questionable evidence base. Ratings provided by experts suggest areas that may benefit from public health education to correct myths and promote healthy sleep.

    [–] Snoring is harmless. Five hours of sleep is enough. Alcohol before bed helps. These are all sleep myths debunked as false in a new study published in the National Sleep Foundation's journal Sleep Health. mvea 3 points ago in science

    The title of the post is a copy and paste from the first paragraph of the linked popular news article here:

    Snoring is harmless. Five hours of sleep is enough. Alcohol before bed helps. These are all sleep myths debunked as false in a peer-reviewed study published Tuesday in National Sleep Foundation's journal Sleep Health.

    Journal Reference:

    Sleep myths: an expert-led study to identify false beliefs about sleep that impinge upon population sleep health practices

    Rebecca Robbins, PhDa,low asterisk,correspondenceEmail the author PhD Rebecca Robbins, Michael A. Grandner, PhDb, Orfeu M. Buxton, PhDc,j,k,l, Lauren Hale, PhDd, Daniel J. Buysse, MDe, Kristen L. Knutson, PhDf, Sanjay R. Patel, MDg, Wendy M. Troxel, PhDh, Shawn D. Youngstedt, PhDi, Charles A. Czeisler, PhD, MD, FRCPj,k, Girardin Jean-Louis, PhDa

    Sleep Health

    Published Online: April 16, 2019

    Link: https://www.sleephealthjournal.org/#/article/S2352-7218(19)30025-7/fulltext

    Doi: https://doi.org/10.1016/j.sleh.2019.02.002

    Abstract

    Introduction

    False beliefs about sleep can persist despite contradicting scientific evidence, potentially impairing population health. Identifying commonly held false beliefs lacking an evidence base (“myths”) can inform efforts to promote population sleep health.

    Method

    We compiled a list of potential myths using Internet searches of popular press and scientific literature. We used a Delphi process with sleep experts (n = 10) from the fields of sleep medicine and research. Selection and refinement of myths by sleep experts proceeded in 3 phases, including focus groups (Phase 1); email-based feedback to edit, add, or remove myths (Phase 2); and closed-ended questionnaires (Phase 3) where experts rated myths on 2 dimensions, falseness and public health significance, using 5-point Likert scale from 1 (“not at all”) to 5 (“extremely false”).

    Results

    The current study identified 20 sleep myths. Mean expert ratings of falseness ranged from 5.00 (SD = 0.00) for the statement “during sleep the brain is not active” to 2.50 (SD = 1.07) for the statement “sleeping in during the weekends is a good way to ensure you get adequate sleep.” Mean responses to public health significance ranged from 4.63 (SD = 0.74) for debunking the statement that “many adults need only 5 or less hours of sleep for general health” to 1.71 (SD = 0.49) for the statement that “remembering your dreams is a sign of a good night's sleep.”

    Conclusion

    The current study identified commonly held sleep myths that have a limited or questionable evidence base. Ratings provided by experts suggest areas that may benefit from public health education to correct myths and promote healthy sleep.

    [–] People often say they can get by on five or fewer hours of sleep, that snoring is harmless, and that having a drink helps you to fall asleep. These are, in fact, myths about sleeping that not only shape poor habits, but may also pose a significant public health threat, according to a new study. mvea 1 points ago in science

    The title of the post is a copy and paste from the first two paragraphs of the linked academic press release here:

    People often say they can get by on five or fewer hours of sleep, that snoring is harmless, and that having a drink helps you to fall asleep.

    These are, in fact, among the most widely held myths about sleeping that not only shape poor habits, but may also pose a significant public health threat, according to a new study published online April 16 in Sleep Health.

    Journal Reference:

    Sleep myths: an expert-led study to identify false beliefs about sleep that impinge upon population sleep health practices

    Rebecca Robbins, PhDa,low asterisk,correspondenceEmail the author PhD Rebecca Robbins, Michael A. Grandner, PhDb, Orfeu M. Buxton, PhDc,j,k,l, Lauren Hale, PhDd, Daniel J. Buysse, MDe, Kristen L. Knutson, PhDf, Sanjay R. Patel, MDg, Wendy M. Troxel, PhDh, Shawn D. Youngstedt, PhDi, Charles A. Czeisler, PhD, MD, FRCPj,k, Girardin Jean-Louis, PhDa

    Sleep Health

    Published Online: April 16, 2019

    Link: https://www.sleephealthjournal.org/#/article/S2352-7218(19)30025-7/fulltext

    Doi: https://doi.org/10.1016/j.sleh.2019.02.002

    Abstract

    Introduction

    False beliefs about sleep can persist despite contradicting scientific evidence, potentially impairing population health. Identifying commonly held false beliefs lacking an evidence base (“myths”) can inform efforts to promote population sleep health.

    Method

    We compiled a list of potential myths using Internet searches of popular press and scientific literature. We used a Delphi process with sleep experts (n = 10) from the fields of sleep medicine and research. Selection and refinement of myths by sleep experts proceeded in 3 phases, including focus groups (Phase 1); email-based feedback to edit, add, or remove myths (Phase 2); and closed-ended questionnaires (Phase 3) where experts rated myths on 2 dimensions, falseness and public health significance, using 5-point Likert scale from 1 (“not at all”) to 5 (“extremely false”).

    Results

    The current study identified 20 sleep myths. Mean expert ratings of falseness ranged from 5.00 (SD = 0.00) for the statement “during sleep the brain is not active” to 2.50 (SD = 1.07) for the statement “sleeping in during the weekends is a good way to ensure you get adequate sleep.” Mean responses to public health significance ranged from 4.63 (SD = 0.74) for debunking the statement that “many adults need only 5 or less hours of sleep for general health” to 1.71 (SD = 0.49) for the statement that “remembering your dreams is a sign of a good night's sleep.”

    Conclusion

    The current study identified commonly held sleep myths that have a limited or questionable evidence base. Ratings provided by experts suggest areas that may benefit from public health education to correct myths and promote healthy sleep.

    [–] People often say they can get by on five or fewer hours of sleep, that snoring is harmless, and that having a drink helps you to fall asleep. These are, in fact, myths about sleeping that not only shape poor habits, but may also pose a significant public health threat, according to a new study. mvea 1 points ago in Health

    The title of the post is a copy and paste from the first two paragraphs of the linked academic press release here:

    People often say they can get by on five or fewer hours of sleep, that snoring is harmless, and that having a drink helps you to fall asleep.

    These are, in fact, among the most widely held myths about sleeping that not only shape poor habits, but may also pose a significant public health threat, according to a new study published online April 16 in Sleep Health.

    Journal Reference:

    Sleep myths: an expert-led study to identify false beliefs about sleep that impinge upon population sleep health practices

    Rebecca Robbins, PhDa,low asterisk,correspondenceEmail the author PhD Rebecca Robbins, Michael A. Grandner, PhDb, Orfeu M. Buxton, PhDc,j,k,l, Lauren Hale, PhDd, Daniel J. Buysse, MDe, Kristen L. Knutson, PhDf, Sanjay R. Patel, MDg, Wendy M. Troxel, PhDh, Shawn D. Youngstedt, PhDi, Charles A. Czeisler, PhD, MD, FRCPj,k, Girardin Jean-Louis, PhDa

    Sleep Health

    Published Online: April 16, 2019

    Link: https://www.sleephealthjournal.org/#/article/S2352-7218(19)30025-7/fulltext

    Doi: https://doi.org/10.1016/j.sleh.2019.02.002

    Abstract

    Introduction

    False beliefs about sleep can persist despite contradicting scientific evidence, potentially impairing population health. Identifying commonly held false beliefs lacking an evidence base (“myths”) can inform efforts to promote population sleep health.

    Method

    We compiled a list of potential myths using Internet searches of popular press and scientific literature. We used a Delphi process with sleep experts (n = 10) from the fields of sleep medicine and research. Selection and refinement of myths by sleep experts proceeded in 3 phases, including focus groups (Phase 1); email-based feedback to edit, add, or remove myths (Phase 2); and closed-ended questionnaires (Phase 3) where experts rated myths on 2 dimensions, falseness and public health significance, using 5-point Likert scale from 1 (“not at all”) to 5 (“extremely false”).

    Results

    The current study identified 20 sleep myths. Mean expert ratings of falseness ranged from 5.00 (SD = 0.00) for the statement “during sleep the brain is not active” to 2.50 (SD = 1.07) for the statement “sleeping in during the weekends is a good way to ensure you get adequate sleep.” Mean responses to public health significance ranged from 4.63 (SD = 0.74) for debunking the statement that “many adults need only 5 or less hours of sleep for general health” to 1.71 (SD = 0.49) for the statement that “remembering your dreams is a sign of a good night's sleep.”

    Conclusion

    The current study identified commonly held sleep myths that have a limited or questionable evidence base. Ratings provided by experts suggest areas that may benefit from public health education to correct myths and promote healthy sleep.

    [–] Scientists restore metabolic activity to cells of the brains of dead pigs mvea 1 points ago in Futurology

    Thanks for contributing. However, your submission was removed from /r/Futurology

    Rule 9 - Avoid posting content that is a duplicate of content posted within the last 7 days.

    https://www.reddit.com/r/Futurology/comments/beacq1/pig_brains_partially_revived_after_death/

    Refer to the subreddit rules, the transparency wiki, or the domain blacklist for more information

    Message the Mods if you feel this was in error

    [–] Scientists Restore Some Function In The Brains Of Dead Pigs mvea 1 points ago in Futurology

    Thanks for contributing. However, your submission was removed from /r/Futurology

    Rule 9 - Avoid posting content that is a duplicate of content posted within the last 7 days.

    https://www.reddit.com/r/Futurology/comments/beacq1/pig_brains_partially_revived_after_death/

    Refer to the subreddit rules, the transparency wiki, or the domain blacklist for more information

    Message the Mods if you feel this was in error

    [–] Scientists: We kept pig brains alive 10 hours after death. Bioethicists: “Holy shit.” mvea 1 points ago in Futurology

    Thanks for contributing. However, your submission was removed from /r/Futurology

    Rule 9 - Avoid posting content that is a duplicate of content posted within the last 7 days.

    https://www.reddit.com/r/Futurology/comments/beacq1/pig_brains_partially_revived_after_death/

    Refer to the subreddit rules, the transparency wiki, or the domain blacklist for more information

    Message the Mods if you feel this was in error

    [–] ‘Partly Alive’: Scientists Revive Cells in Brains From Dead Pigs mvea 1 points ago in Futurology

    Thanks for contributing. However, your submission was removed from /r/Futurology

    Rule 9 - Avoid posting content that is a duplicate of content posted within the last 7 days.

    https://www.reddit.com/r/Futurology/comments/beacq1/pig_brains_partially_revived_after_death/

    Refer to the subreddit rules, the transparency wiki, or the domain blacklist for more information

    Message the Mods if you feel this was in error

    [–] Artificial intelligence accelerates efforts to develop clean, virtually limitless fusion energy, with scientists using deep learning for the first time to forecast sudden disruptions that can halt fusion reactions, in a new study published in the journal Nature. mvea 1 points ago in Futurology

    The title of the post is a copy and paste from the title and first paragraph of the linked academic press release here:

    Artificial intelligence accelerates efforts to develop clean, virtually limitless fusion energy

    A major step in this direction is under way at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) and Princeton University, where a team of scientists working with a Harvard graduate student is for the first time applying deep learning — a powerful new version of the machine learning form of AI — to forecast sudden disruptions that can halt fusion reactions and damage the doughnut-shaped tokamaks that house the reactions.

    Journal Reference:

    Predicting disruptive instabilities in controlled fusion plasmas through deep learning

    Julian Kates-Harbeck, Alexey Svyatkovskiy & William Tang

    Nature (2019)

    Link: https://www.nature.com/articles/s41586-019-1116-4

    DOI: https://doi.org/10.1038/s41586-019-1116-4

    Abstract

    Nuclear fusion power delivered by magnetic-confinement tokamak reactors holds the promise of sustainable and clean energy1. The avoidance of large-scale plasma instabilities called disruptions within these reactors2,3 is one of the most pressing challenges4,5, because disruptions can halt power production and damage key components. Disruptions are particularly harmful for large burning-plasma systems such as the multibillion-dollar International Thermonuclear Experimental Reactor (ITER) project6 currently under construction, which aims to be the first reactor that produces more power from fusion than is injected to heat the plasma. Here we present a method based on deep learning for forecasting disruptions. Our method extends considerably the capabilities of previous strategies such as first-principles-based5 and classical machine-learning7,8,9,10,11 approaches. In particular, it delivers reliable predictions for machines other than the one on which it was trained—a crucial requirement for future large reactors that cannot afford training disruptions. Our approach takes advantage of high-dimensional training data to boost predictive performance while also engaging supercomputing resources at the largest scale to improve accuracy and speed. Trained on experimental data from the largest tokamaks in the United States (DIII-D12) and the world (Joint European Torus, JET13), our method can also be applied to specific tasks such as prediction with long warning times: this opens up the possibility of moving from passive disruption prediction to active reactor control and optimization. These initial results illustrate the potential for deep learning to accelerate progress in fusion-energy science and, more generally, in the understanding and prediction of complex physical systems.

    [–] Artificial intelligence accelerates efforts to develop clean, virtually limitless fusion energy, with scientists using deep learning for the first time to forecast sudden disruptions that can halt fusion reactions, in a new study published in the journal Nature. mvea 16 points ago in science

    The title of the post is a copy and paste from the title and first paragraph of the linked academic press release here:

    Artificial intelligence accelerates efforts to develop clean, virtually limitless fusion energy

    A major step in this direction is under way at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) and Princeton University, where a team of scientists working with a Harvard graduate student is for the first time applying deep learning — a powerful new version of the machine learning form of AI — to forecast sudden disruptions that can halt fusion reactions and damage the doughnut-shaped tokamaks that house the reactions.

    Journal Reference:

    Predicting disruptive instabilities in controlled fusion plasmas through deep learning

    Julian Kates-Harbeck, Alexey Svyatkovskiy & William Tang

    Nature (2019)

    Link: https://www.nature.com/articles/s41586-019-1116-4

    DOI: https://doi.org/10.1038/s41586-019-1116-4

    Abstract

    Nuclear fusion power delivered by magnetic-confinement tokamak reactors holds the promise of sustainable and clean energy1. The avoidance of large-scale plasma instabilities called disruptions within these reactors2,3 is one of the most pressing challenges4,5, because disruptions can halt power production and damage key components. Disruptions are particularly harmful for large burning-plasma systems such as the multibillion-dollar International Thermonuclear Experimental Reactor (ITER) project6 currently under construction, which aims to be the first reactor that produces more power from fusion than is injected to heat the plasma. Here we present a method based on deep learning for forecasting disruptions. Our method extends considerably the capabilities of previous strategies such as first-principles-based5 and classical machine-learning7,8,9,10,11 approaches. In particular, it delivers reliable predictions for machines other than the one on which it was trained—a crucial requirement for future large reactors that cannot afford training disruptions. Our approach takes advantage of high-dimensional training data to boost predictive performance while also engaging supercomputing resources at the largest scale to improve accuracy and speed. Trained on experimental data from the largest tokamaks in the United States (DIII-D12) and the world (Joint European Torus, JET13), our method can also be applied to specific tasks such as prediction with long warning times: this opens up the possibility of moving from passive disruption prediction to active reactor control and optimization. These initial results illustrate the potential for deep learning to accelerate progress in fusion-energy science and, more generally, in the understanding and prediction of complex physical systems.