15 datasets found
  1. d

    Data from: Why bears hibernate? Redefining the scaling energetics of...

    • search.dataone.org
    • datadryad.org
    Updated May 17, 2025
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    Roberto Nespolo (2025). Why bears hibernate? Redefining the scaling energetics of hibernation [Dataset]. http://doi.org/10.5061/dryad.0cfxpnw4j
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    Dataset updated
    May 17, 2025
    Dataset provided by
    Dryad Digital Repository
    Authors
    Roberto Nespolo
    Time period covered
    Jan 1, 2022
    Description

    Hibernation is a natural state of suspended animation that many mammals experience and has been interpreted as an adaptive strategy for saving energy. However, the actual amount of savings that hibernation represents, and particularly its dependence on body mass (the “scaling†) has not been calculated properly. Here we estimated the scaling of daily energy expenditure of hibernation (DEEH), covering a range of five orders of magnitude in mass. We found that DEEH scales isometrically with mass, which means that a gram of hibernating bat has a similar metabolism to that of a gram of bear, 20,000 times larger. Given that the metabolic rate of active animals scales allometrically, the point where these scaling curves intersect with DEEH represents the mass where energy savings by hibernation are zero. For BMR, these zero savings are attained for a relatively small bear (~100 kg). Calculated on a per-cell basis, the cellular metabolic power of hibernation was estimated to be 1.3x10-12 ± 2.6x...

  2. API Usage Databases

    • figshare.com
    bin
    Updated Jan 19, 2016
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    Anand Sawant; Alberto Bacchelli (2016). API Usage Databases [Dataset]. http://doi.org/10.6084/m9.figshare.1320591.v9
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    binAvailable download formats
    Dataset updated
    Jan 19, 2016
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Anand Sawant; Alberto Bacchelli
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset has the database dumps of API usages of APIs such as Guice, Guava, Easymock, Spring and Hibernate.

  3. Scaling of metabolic rate in hibernators: Translation of literature data:...

    • zenodo.org
    • explore.openaire.eu
    • +1more
    doc, xls
    Updated Aug 5, 2022
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    Øivind Tøien; Øivind Tøien; Brian M. Barnes; Thomas Ruf; Brian M. Barnes; Thomas Ruf (2022). Scaling of metabolic rate in hibernators: Translation of literature data: For a comment to Nespolo et al. (2022) [Dataset]. http://doi.org/10.5061/dryad.msbcc2g1w
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    doc, xlsAvailable download formats
    Dataset updated
    Aug 5, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Øivind Tøien; Øivind Tøien; Brian M. Barnes; Thomas Ruf; Brian M. Barnes; Thomas Ruf
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    This spreadsheet provides a translation of data from the literature for the manuscript: Do bears hibernate in the woods? Comment on 'Why bears hibernate? Redefining the scaling energetics of hibernation', and includes both the background data for Figure 1 which is presented in the manuscript.

    Full reference for article it is commented on: Nespolo, R. F., Mejias, C., and Bozinovic, F. Why bears hibernate? Redefining the scaling energetics of hibernation. Proc. R. Soc. B. 2022; 289(1973):20220456. We have made corrections to the data in the original article's Table S1, and translated empirical BMR data from literature instead of calculating a regression line from White, C.R. & Seymour, R.S. (2003). This changes the body mass where regression lines for Log (DDEHIB) and Log(BMR) cross, and thus where no savings from hibernation can be expected, from 75 kg to over 2,250 kg and shows that bears hibernate to save energy.

  4. d

    Data from: Hibernating female big brown bats (Eptesicus fuscus) adjust...

    • search.dataone.org
    • data.niaid.nih.gov
    • +1more
    Updated Aug 9, 2024
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    Kristina Muise; Yvonne Dzal; Quinn Fletcher; Craig Willis (2024). Hibernating female big brown bats (Eptesicus fuscus) adjust huddling and drinking behaviour, but not arousal frequency, in response to low humidity [Dataset]. http://doi.org/10.5061/dryad.pc866t1wg
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    Dataset updated
    Aug 9, 2024
    Dataset provided by
    Dryad Digital Repository
    Authors
    Kristina Muise; Yvonne Dzal; Quinn Fletcher; Craig Willis
    Time period covered
    Jan 1, 2024
    Description

    Many mammals hibernate during winter, reducing energy expenditure via bouts of torpor. The majority of a hibernator’s energy reserves are used to fuel brief, but costly, arousals from torpor. Although arousals likely serve multiple functions, an important one is to restore water stores depleted during torpor. Many hibernating bat species require high humidity, presumably to reduce torpid water loss, but big brown bats (Eptesicus fuscus) appear tolerant of a wide humidity range. We tested the hypothesis that hibernating female E. fuscus use behavioural flexibility during torpor and arousals to maintain water balance and reduce energy expenditure. We predicted: (1) E. fuscus hibernating in dry conditions would exhibit more compact huddles during torpor and drink more frequently than bats in high humidity conditions; and (2) frequency and duration of torpor bouts and arousals, and thus, total loss of body mass would not differ between bats in both environments. We housed hibernating E. fus..., , , # Hibernating female big brown bats (Eptesicus fuscus) adjust huddling and drinking behaviour, but not arousal frequency, in response to low humidity

    Description of the data and file structure

    The excel file has four different sheets that contains (listed in order):

    Sheet1_Video Data - arousals: arousal begin and end time/date, bat ID, humidity treatment, drinking bouts, and associated starting body mass (prior to hibernation) and ending body mass (end of hibernation))

    Sheet2_Video Data - torpor: torpor begin and end time/date, bat ID, humidity treatment, and associated starting body mass (prior to hibernation) and ending body mass (end of hibernation))

    Sheet3_Arousal Definition Data: bat ID, humidity treatment, arousal begining and end data/time, and associated skin temperature threshold. Note: arousals for video data do not have an associated skin temperature threshold.

    Sheet4_Huddle Size Index: photo date and time, humidity treatment, file name, and huddle ...

  5. d

    Data from: Life history consequences of climate change in hibernating...

    • datadryad.org
    • search.dataone.org
    zip
    Updated Jul 25, 2022
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    Caitlin Wells; Rebecca Barbier; Shelley Nelson; Rachel Kanaziz; Lise Aubry (2022). Life history consequences of climate change in hibernating mammals: A review [Dataset]. http://doi.org/10.5061/dryad.z34tmpggs
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    zipAvailable download formats
    Dataset updated
    Jul 25, 2022
    Dataset provided by
    Dryad
    Authors
    Caitlin Wells; Rebecca Barbier; Shelley Nelson; Rachel Kanaziz; Lise Aubry
    Time period covered
    2022
    Description

    Please see ReadMe file

  6. Hibernate Import Data from United States - Seair.co.in

    • seair.co.in
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    Seair Exim, Hibernate Import Data from United States - Seair.co.in [Dataset]. https://www.seair.co.in
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    .bin, .xml, .csv, .xlsAvailable download formats
    Dataset provided by
    Seair Exim Solutions
    Authors
    Seair Exim
    Area covered
    United States
    Description

    Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

  7. Data from: Why hibernate? Tests of four hypotheses to explain intraspecific...

    • figshare.com
    xlsx
    Updated May 30, 2023
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    Austin Allison; Courtney Conway; Alice Morris (2023). Data from: Why hibernate? Tests of four hypotheses to explain intraspecific variation in hibernation phenology [Dataset]. http://doi.org/10.6084/m9.figshare.20961016.v2
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    xlsxAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Austin Allison; Courtney Conway; Alice Morris
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset includes hibernation phenology (immergence date, emergence date, and hibernation duration) for northern Idaho ground squirrels (Urocitellus brunneus), along with data used as predictor variables in linear mixed-effects models designed to explain intraspecific variation in the three hibernation behaviors. Code for that lme analysis is also included. Also included in this dataset are body mass data for northern Idaho ground squirrels, the code used to generate predicted squirrel body mass curves, NDVI data for northern Idaho ground squirrel study sites, and the code used to generate predicted NDVI curves for those sites. The data files include metadata sheets to better explain the data and its collection.

  8. f

    Data for Female hormonal profiles and vaginal cytology in a ground squirrel...

    • figshare.com
    docx
    Updated Nov 14, 2023
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    Nina Vasilieva; Natalia Tikhonova; Ludmila Savinetskaya; Ekaterina Kuznetsova (2023). Data for Female hormonal profiles and vaginal cytology in a ground squirrel species with prolonged hibernation [Dataset]. http://doi.org/10.6084/m9.figshare.24294988.v1
    Explore at:
    docxAvailable download formats
    Dataset updated
    Nov 14, 2023
    Dataset provided by
    figshare
    Authors
    Nina Vasilieva; Natalia Tikhonova; Ludmila Savinetskaya; Ekaterina Kuznetsova
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Hibernating mammals have annual cycles with strict timing of all processes including reproduction; yet female reproductive physiology is poorly studied in these species. We investigated the estrous cycle in yellow ground squirrels (Spermophilus fulvus), which hibernate up to 9 months. On the basis of vaginal cytology and serum progesterone and estradiol profiles, we identified proestrus, estrus, metestrus, and anestrus in the cycle. Similarly to other rodents, predominance of cornified cells marked estrus, and an increase in the leukocyte number reflected metestrus. The only estrus in a year started and then pregnancy occurred mostly within 3 days after the spring emergence. In one female, we noticed a copulatory plug for the first time for this species. The progesterone level increased from proestrus/estrus to pregnancy and decreased in the postlactation period. Estradiol concentration did not change significantly throughout the estrous cycle but varied among females and was consistently high in some of them. The hormone levels did not vary with female age despite smaller body size in yearling females as compared with older ones. During postlactation, progesterone concentration diminished toward hibernation, and we failed to detect signs of prehibernation activation of the female reproductive system. Probably, gonadal preparation in S. fulvus females proceeds at periodic arousals during hibernation. Our data showed fast transitions between phases of the female estrous cycle and early maturation of juvenile females, thus supporting the hypothesis of fast life history strategy of S. fulvus.

  9. I

    Global Java Web Frameworks Software Market Key Success Factors 2025-2032

    • statsndata.org
    excel, pdf
    Updated May 2025
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    Stats N Data (2025). Global Java Web Frameworks Software Market Key Success Factors 2025-2032 [Dataset]. https://www.statsndata.org/report/java-web-frameworks-software-market-96994
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    pdf, excelAvailable download formats
    Dataset updated
    May 2025
    Dataset authored and provided by
    Stats N Data
    License

    https://www.statsndata.org/how-to-orderhttps://www.statsndata.org/how-to-order

    Area covered
    Global
    Description

    The Java Web Frameworks Software market plays a pivotal role in the development of dynamic and robust web applications in today's digital landscape. As businesses increasingly demand scalable, secure, and high-performance solutions, Java web frameworks, such as Spring, JSF, and Hibernate, have emerged as essential t

  10. n

    Energetics meets sexual conflict: the phenology of hibernation in Tasmanian...

    • data.niaid.nih.gov
    • datadryad.org
    zip
    Updated Sep 13, 2019
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    Stewart C. Nicol; Gemma E. Morrow; Rachel L. Harris (2019). Energetics meets sexual conflict: the phenology of hibernation in Tasmanian echidnas (Tachyglossus aculeatus setosus) [Dataset]. http://doi.org/10.5061/dryad.th70gn0
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    zipAvailable download formats
    Dataset updated
    Sep 13, 2019
    Authors
    Stewart C. Nicol; Gemma E. Morrow; Rachel L. Harris
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    Australia, Tasmania
    Description
    1. Echidnas are egg-laying mammals found across Australia and in Tasmania they hibernate resulting in a most unusual mating system: males enter hibernation in late summer-early autumn and arouse in late autumn-early winter to mate, although females are still hibernating. Groups of males compete for matings and both males and females mate with multiple partners. Females that mate early return to hibernation even when pregnant, and males continue to mate with pregnant females. We asked to what extent to can the bizarre combination of behavioural and physiological features that characterize reproduction of Tasmanian echidnas be attributed to their phylogeny, and how much is a consequence of their ecology? 2. To understand the interaction between energetics and the echidna mating system in determining the timing of echidna hibernation we analysed data from an 18-year study of a wild population of Tasmanian echidnas 3. Males with high fat reserves arouse earliest and seek out suitable females, and females that mate early in the mating season re-enter hibernation while pregnant. 4. Competition between males drives early mating and while mating with males in the best condition could be advantageous for females and their young, egg-laying in winter is potentially disadvantageous, and post-mating hibernation by females is a means of delaying hatching of young until environmental conditions are more favourable. This post-mating hibernation by females is usually disrupted by males which mate with them although they are already pregnant.
    2. Comparisons with other echidna populations suggests that a decreased activity period due to hibernation has not increased male-male competition. 6. Similar competition between groups of males for access to females is seen in chlamyphorid armadillos, which occupy a similar ecological niche to echidnas.
  11. R

    Data from: Software Architecture of the OLA Observatory Information System...

    • entrepot.recherche.data.gouv.fr
    Updated Aug 1, 2021
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    Antoine Schellenberger; Denis Barbet; Damien Maurice; Guillaume Enrico; Amélie Fiocca; Ghislaine Monet; Ghislaine Monet; Antoine Schellenberger; Denis Barbet; Damien Maurice; Guillaume Enrico; Amélie Fiocca (2021). Software Architecture of the OLA Observatory Information System for Lake Environmental Research [Dataset]. http://doi.org/10.15454/VBWYWG
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    Dataset updated
    Aug 1, 2021
    Dataset provided by
    Recherche Data Gouv
    Authors
    Antoine Schellenberger; Denis Barbet; Damien Maurice; Guillaume Enrico; Amélie Fiocca; Ghislaine Monet; Ghislaine Monet; Antoine Schellenberger; Denis Barbet; Damien Maurice; Guillaume Enrico; Amélie Fiocca
    License

    https://spdx.org/licenses/etalab-2.0.htmlhttps://spdx.org/licenses/etalab-2.0.html

    Description

    OLA Information system (©SOERE OLA-IS, AnaEE-France, INRA Thonon-les-Bains, developed by Eco-Informatics ORE INRA Team) has been developed to meet data management needs of lake environmental research observatories in order to make data available for scientific communities. Software architecture of this IS is structured around (i) a shared central component dedicated to generic functions and (ii) modular components specific to lake thematics. The creation of the IS is done by inheriting the core component and using the appropriate modular components. SI is developed with the Java language (version 8). The components are Java projects that follow the structuring of a "multi-module" Maven project. The web interfaces are developed by using the framework JSF with Primefaces user interface component library. Spring and Hibernate frameworks complete the development tools. PostgreSQL is the relational database management system used. (2019-01-18). This information system makes it possible to store and make available physico-chemical data, biodiversity data (phytoplankton, zooplankton, fishes), data from multiparameter probes, chlorophyll, primary production, etc.

  12. Table 1. Xper 3 in An Xper 3 reference guide for taxonomists: a...

    • zenodo.org
    html
    Updated Apr 22, 2025
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    Adeline Kerner; Elie Mario Saliba; Sylvain Bouquin; Rémy Portier; Régine Vignes-Lebbe; Adeline Kerner; Elie Mario Saliba; Sylvain Bouquin; Rémy Portier; Régine Vignes-Lebbe (2025). Table 1. Xper 3 in An Xper 3 reference guide for taxonomists: a collaborative system for identification keys and descriptive data [Dataset]. http://doi.org/10.5281/zenodo.15264611
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    htmlAvailable download formats
    Dataset updated
    Apr 22, 2025
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Adeline Kerner; Elie Mario Saliba; Sylvain Bouquin; Rémy Portier; Régine Vignes-Lebbe; Adeline Kerner; Elie Mario Saliba; Sylvain Bouquin; Rémy Portier; Régine Vignes-Lebbe
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Table 1. Xper3 technical architecture.

    Data storageRelational database Maria DB
    Object/Relational MappingHibernate framework
    Frontend interfaceHTML, Ajax, jQuery and Spring framework
    Exchange formatsCSV, SDD (XML)
    Identification servicesREST-type services
    Backend codeJava

  13. R

    Software architecture for environnemental research observatories information...

    • entrepot.recherche.data.gouv.fr
    Updated Aug 5, 2021
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    Antoine Schellenberger; Philippe Tcherniatinsky; Vivianne-Judith Yayende-Guedoka; Rachid Yahiaoui; Damien Maurice; Ghislaine Monet; Antoine Schellenberger; Philippe Tcherniatinsky; Vivianne-Judith Yayende-Guedoka; Rachid Yahiaoui; Damien Maurice; Ghislaine Monet (2021). Software architecture for environnemental research observatories information systems: central component [Dataset]. http://doi.org/10.15454/QJJJZU
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    Dataset updated
    Aug 5, 2021
    Dataset provided by
    Recherche Data Gouv
    Authors
    Antoine Schellenberger; Philippe Tcherniatinsky; Vivianne-Judith Yayende-Guedoka; Rachid Yahiaoui; Damien Maurice; Ghislaine Monet; Antoine Schellenberger; Philippe Tcherniatinsky; Vivianne-Judith Yayende-Guedoka; Rachid Yahiaoui; Damien Maurice; Ghislaine Monet
    License

    https://spdx.org/licenses/etalab-2.0.htmlhttps://spdx.org/licenses/etalab-2.0.html

    Description

    Information systems have been developed to meet data management needs of environmental research observatories in order to make data available for scientific communities. Software architecture of these IS is structured around (i) a central component dedicated to generic functions shared by all IS and (ii) modular components specific to the environmental themes studied by the observatories. The creation of the IS is done by inheriting the core component and using the appropriate modular components. SI are developed with the Java language (version 8). The components are Java projects that follow the structuring of a "multi-module" Maven project. The web interfaces are developed by using the framework JSF with Primefaces user interface component library. Spring and Hibernate frameworks complete the development tools. PostgreSQL is the relational database management system used. Information system are developed by Eco-Informatics ORE INRA Team, AnaEE-France

  14. c

    Associated data for Innovate, Hibernate, Liquidate – The Motivation of...

    • acquire.cqu.edu.au
    Updated Jan 25, 2024
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    Nicole Griffiths (2024). Associated data for Innovate, Hibernate, Liquidate – The Motivation of Female Entrepreneurs in Regional Western Australia During Times of Crisis. [Dataset]. http://doi.org/10.25946/24873306.v1
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    Dataset updated
    Jan 25, 2024
    Dataset provided by
    CQUniversity
    Authors
    Nicole Griffiths
    License

    https://rightsstatements.org/page/InC/1.0/?language=enhttps://rightsstatements.org/page/InC/1.0/?language=en

    Area covered
    Australia, Western Australia
    Description

    The purpose of this research was to investigate how COVID-19 motivated female entrepreneurs in regional Western Australia to innovate, hibernate or liquidate their business; explore outcomes of any changes they made to their business as a result of the pandemic; and explore how COVID-19 affected their motivations towards their business.

  15. Impact of COVID-19 on consumer spending behavior India 2020

    • statista.com
    Updated Mar 17, 2022
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    Statista (2022). Impact of COVID-19 on consumer spending behavior India 2020 [Dataset]. https://www.statista.com/statistics/1195838/india-impact-of-covid-19-on-consumer-spending-behavior/
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    Dataset updated
    Mar 17, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    May 2020
    Area covered
    India
    Description

    In a survey conducted in May 2020, regarding the impact of coronavirus (COVID-19) on consumer spending behavior in India, 38 percent of the respondents showed concern about the pandemic and preferred to hibernate and spend. About 35 percent of the respondents were hit quite hard by the pandemic and as a result decided to cut down their spending by a large extent.

  16. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Roberto Nespolo (2025). Why bears hibernate? Redefining the scaling energetics of hibernation [Dataset]. http://doi.org/10.5061/dryad.0cfxpnw4j

Data from: Why bears hibernate? Redefining the scaling energetics of hibernation

Related Article
Explore at:
Dataset updated
May 17, 2025
Dataset provided by
Dryad Digital Repository
Authors
Roberto Nespolo
Time period covered
Jan 1, 2022
Description

Hibernation is a natural state of suspended animation that many mammals experience and has been interpreted as an adaptive strategy for saving energy. However, the actual amount of savings that hibernation represents, and particularly its dependence on body mass (the “scaling†) has not been calculated properly. Here we estimated the scaling of daily energy expenditure of hibernation (DEEH), covering a range of five orders of magnitude in mass. We found that DEEH scales isometrically with mass, which means that a gram of hibernating bat has a similar metabolism to that of a gram of bear, 20,000 times larger. Given that the metabolic rate of active animals scales allometrically, the point where these scaling curves intersect with DEEH represents the mass where energy savings by hibernation are zero. For BMR, these zero savings are attained for a relatively small bear (~100 kg). Calculated on a per-cell basis, the cellular metabolic power of hibernation was estimated to be 1.3x10-12 ± 2.6x...

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