Nippon Eiyo Shokuryo Gakkaishi
Japanese Society of Nutrition and Food Science
ISSN:
02873516, 18832849
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journal names
Nippon Eiyo Shokuryo Gakkaishi
Top-3 citing journals
Journal of Nutritional Science and Vitaminology
(132 citations)

Food Science and Technology Research
(102 citations)
Nippon Shokuhin Kagaku Kogaku Kaishi
(101 citations)
Top-3 organizations

University of Tokyo
(61 publications)

Tokyo University of Agriculture
(53 publications)

Kyoto University
(47 publications)

Tokyo University of Agriculture
(8 publications)

Nagoya University
(6 publications)

Kyoto University
(5 publications)
Top-3 countries
Most cited in 5 years
Found
Publications found: 4591
Q1

Microwave sea ice and ocean brightness temperature and emissivity between 22 and 243 GHz from ship-based radiometers
Rückert J.E., Walbröl A., Risse N., Krobot P., Haseneder-Lind R., Mech M., Ebell K., Spreen G.
Abstract
Passive microwave measurements of Arctic sea ice have been conducted over the last 50 years from space and during airborne, ship- and ground-based measurement campaigns. The different radiometric signatures of distinct surface types have led to satellite retrievals of, e.g., sea-ice concentration. In contrast, ground-based upward-viewing radiometers measure radiation emitted from the atmosphere and are used to retrieve atmospheric variables. Here, we present results from a ship-based radiometer setup with a mirror construction, which allows us to switch between atmospheric and surface measurements flexibly. This way, in summer 2022, surface observations in the Arctic marginal sea-ice zone could be performed from the research vessel Polarstern by two radiometers covering the frequency range from 22 to 243 GHz. At low frequencies, the brightness temperatures show clear signatures of different surface conditions. We estimate emissivities at 53∘ zenith angle from infrared-based skin temperatures. Predominantly vertically polarized 22–31 GHz emissivities are between 0.51 and 0.55 for open ocean and around 0.95 for sea ice. Predominantly horizontally polarized 243 GHz ocean emissivities are around 0.78 and ice surfaces exhibit a large variability from 0.67 to 0.82. Our results can improve the characterization of surface emissions in satellite retrieval algorithms.
Q1

Characteristics, origin, and significance of chessboard subgrain boundaries in the WAIS Divide Ice Core
Fitzpatrick J.J., Wilen L.A., Voigt D.E., Alley R.B., Fegyveresi J.M.
Q1

Distributed energy balance, mass balance and climate sensitivity of upper Chandra Basin glaciers, western Himalaya
Oulkar S.N., Sharma P., Pratap B., Thamban M., Laha S., Patel L.K., Singh A.T.
Abstract
Glacier and snow melt are the primary sources of water for streams, and rivers in upper Indus region of the western Himalaya. However, the magnitude of runoff from this glacierized basin is expected to vary with the available energy in the catchment. Here, we used a physically based energy balance model to estimate the surface energy and surface mass balance (SMB) of the upper Chandra Basin glaciers for 7 hydrological years from 2015 to 2022. A strong seasonality is observed, with net radiation being the dominant energy flux in the summer, while latent and sensible heat flux dominated in the winter. The estimated mean annual SMB of the upper Chandra Basin glaciers is −0.51 ± 0.28 m w.e. a−1, with a cumulative SMB of −3.54 m w.e during 7 years from 2015 to 2022. We find that the geographical factors like aspect, slope, size and elevation of the glacier contribute towards the spatial variability of SMB within the study region. The findings reveal that a 42% increase in precipitation is necessary to counteract the additional mass loss resulting from a 1°C increase in air temperature for the upper Chandra Basin glaciers.
Q1

Forecasting Arctic sea ice drift: insights from two case studies
Valisuo I., Tietsche S.
Abstract
The two main large-scale features of Arctic sea-ice drift are the Beaufort Gyre and the Transpolar Drift Stream. They exhibit strong intraseasonal and interannual variability. Winter 2016/17 showed increased cyclone activity, leading to the collapse of the Beaufort Sea high and the reversal of the Beaufort Gyre. Winter 2020/21 displayed decreased cyclone activity and intense anticyclonic ice transport in the Beaufort Gyre. Here we show that the European Centre for Medium-Range Weather Forecasts’s (ECMWF) extended-range (46 days) retrospective forecasts were able to predict the ice motion during these cases. The initial contrasts in sea level pressure, surface winds and ice drift were well captured, and their temporal evolution—including the reversal of the usual drift direction—well reproduced by the forecasts initialized about a week before the event. Sea-ice thickness in the forecast exhibited initial errors even greater than 1 m that persisted throughout the forecast and negatively affected the ice speed forecast. Despite these shortcomings, the dynamic forecast outperformed the persistence and climatology forecast and represented the observed relation between surface winds and ice drift well. The benefit of dynamic forecasts is especially clear in cases that differ from climatology, like the one we focus on.
Q1

Bragg scattering of surface-gravity waves by an ice shelf with rolling surface morphology
Konovalov Y.V.
Abstract
The propagation of elastic-flexural–gravity waves through an ice shelf is modeled using full three-dimensional elastic models that are coupled with a treatment of under-shelf sea-water flux: (i) finite-difference model (Model 1), (ii) finite-volume model (Model 2) and (iii) depth-integrated finite-difference model (Model 3). The sea-water flow under the ice shelf is described by a wave equation involving the pressure (the sea-water flow is treated as a “potential flow”). Numerical experiments were undertaken for an ice shelf with ‘rolling’ surface morphology, which implies a periodic structure of the ice shelf. The propagation of ocean waves through an ice shelf with rolling surface morphology is accompanied by Bragg scattering (also called Floquet band insulation). The numerical experiments reveal that band gaps resulting from this scattering occur in the dispersion spectra in frequency bands that are consistent with the Bragg’s law. Band gaps render the medium opaque to wave, that is, essentially, the abatement of the incident ocean wave by ice shelf with rolling surface morphology is observed in the models. This abatement explains the ability of preserving of ice shelves like the Ward Hunt Ice Shelf, Ellesmere Island, Canadian Arctic, from the possible resonant-like destroying impact of ocean swell.
Q1

Towards a high-resolution sea ice model: exploring the potential of modelling ice floe fracture with the peridynamic method
Zhang Y., Lu W., Lubbad R., Løset S., Tsarau A., Høyland K.V.
Abstract
Sea-ice deformation is concentrated at linear kinematic features such as ridges and leads. Ridging and leads opening processes are highly related to sea-ice fracture. Different rheology models have been successfully applied in various scenarios. However, most of the approaches adopted are based on continuum mechanics that do not explicitly model fracture processes. There are emerging needs for a more physically informed modelling methods that explicitly address fracture at the kilometre scale. In pursuing this objective, in this paper we explored the potential of applying a promising mesh free numerical method, peridynamics (PD), in modelling ice floe (~km) fractures. PD offers a physically and mathematically consistent theory through which spontaneous emergence and propagation of cracks can be achieved. The integral nature of the governing equations in PD remains valid even if a crack appears. We numerically investigated in this paper the tensile fracture (e.g. lead opening) of an elastic heterogenous ice floe. The modelling results were compared with published numerical results obtained by another numerical method. The potentials and challenges of PD in this application are discussed and summarized.
Q1

Impact of varying solar angles on Arctic iceberg area retrieval from Sentinel-2 near-infrared data
Fisser H., Doulgeris A.P., Høyland K.V.
Abstract
Icebergs are part of the glacial mass balance and they interact with the ocean and with sea ice. Optical satellite remote sensing is often used to retrieve the above-waterline area of icebergs. However, varying solar angles introduce an error to the iceberg area retrieval that had not been quantified. Herein, we approximate the iceberg area error for top-of-atmosphere Sentinel-2 near-infrared data at a range of solar zenith angles. First, we calibrate an iceberg threshold at a
$56^\circ$
solar zenith angle with reference to higher resolution airborne imagery at Storfjorden, Svalbard. A reflectance threshold of 0.12 yields the lowest relative error of 0.19% ± 15.74% and the lowest interquartile spread. Second, we apply the 0.12 reflectance threshold to Sentinel-2 data at 14 solar zenith angles between
$45^\circ$
and
$81^\circ$
in the Kangerlussuaq Fjord, south-east Greenland. Here we quantify the error variation with the solar zenith angle for a consistent set of large icebergs. The error variation is then standardized to the error obtained in Svalbard. Up to a solar zenith angle of
$65^\circ$
, the mean standardized iceberg area error remains between 5.9% and −5.67%. Above
$65^\circ$
, iceberg areas are underestimated and inconsistent, caused by a segregation into shadows and sun-facing slopes.
Q1

Spatiotemporal mass balance variability of Jostedalsbreen ice cap, Norway, revealed by a temperature-index model with data assimilation
Sjursen K.H., Dunse T., Schuler T.V., Andreassen L.M., Åkesson H.
Abstract
Jostedalsbreen in western Norway is the mainland Europe's largest ice cap and a complex system of more than 80 glaciers. While observational records indicate a significant sensitivity to climate fluctuations, knowledge about ice-cap wide spatiotemporal mass changes and their drivers remain sparse. Here, we quantify the surface mass balance (SMB) of Jostedalsbreen from 1960 to 2020 using a temperature-index model within a Bayesian framework. We assimilate seasonal glaciological SMB to constrain accumulation and ablation, and geodetic mass balance to adjust model parameters for each glacier individually. Overall, we find that Jostedalsbreen has experienced a small mass loss of −0.07 m w.e. a−1 (−0.21 to +0.08 m w.e. a−1), but with substantial spatiotemporal variability. Our results suggest that winter SMB variations were the main control on annual SMB between 1960 and 2000, while increasingly negative summer SMB is responsible for substantial mass losses after 2000. Spatial variations in SMB between glaciers or regions of the ice cap are likely associated with local topography and its effect on orographic precipitation. We advocate for models to leverage the growing availability of observational resources to improve SMB predictions. We demonstrate an approach that incorporates complementary datasets, while addressing their inherent uncertainties, to constrain models and provide robust estimates of spatiotemporal SMB and associated uncertainties.
Q1

Open discussion at the IGS symposium on ‘The edges of glaciology’, 7 July 2023
Fowler A.C.
Abstract
There follows the open discussion which took place at the IGS symposium on ‘The Edges of Glaciology’, in July 2023. The discussion was curated by Doug Benn. The time of speaking in minutes and seconds into the Panopto recording is given in bold figures. The recording itself is provided as electronic supplementary material. It has been transcribed and edited by Andrew Fowler, with much (and much-needed) assistance from the participants. Footnotes (mostly references) are editorial intrusions.
Q1

U-net with ResNet-34 backbone for dual-polarized C-band baltic sea-ice SAR segmentation
Karvonen J.
Abstract
In this study, the U-net with ResNet-34, i.e. a residual neural network with 34 layers, backbone semantic segmentation network is applied to C-band sea-ice SAR imagery over the Baltic Sea. Sentinel-1 Extra Wide Swath mode HH/HV-polarized SAR data acquired during the winter season 2018–2019, and corresponding segments derived from the daily Baltic Sea ice charts were used for training the segmentation algorithm. C-band SAR image mosaics of the winter season 2020–2021 were then used to evaluate the segmentation. The major objective was to study the suitability of semantic segmentation of SAR imagery for automated SAR segmentation and also to find a potential replacement for the outdated iterated conditional modes (ICM) algorithm currently in operational use. The results compared to the daily Baltic Sea ice charts and the operational ICM segmentation and visual interpretation were encouraging from the operational point of view. Open water areas were located very well and the oversegmentation produced by ICM was significantly reduced. The correspondence between the ice chart polygons and the segmentation results was also reasonably good. Based on the results, the studied method is a potential candidate to replace the operational ICM SAR segmentation used in the Copernicus Marine Service automated sea-ice products at Finnish Meteorological Institute.
Q1

Comparing heterogeneity of sea ice models with Viscous-Plastic and Maxwell Elasto-Brittle rheology
Bourgett M., Losch M., Plante M.
Abstract
Classical sea-ice models in climate model resolution do not resolve the small-scale physics of sea ice. New methods to address this problem include modifications to established viscous-plastic (VP) rheology models, sub-gridscale parameterizations or new rheologies such as the Maxwell elasto-brittle (MEB) rheology. Here, we investigate differences in gridscale dynamics simulated by the VP and MEB models, their dependency on tunable model parameters and their response to added stochastic perturbations of material parameters in a new implementation in the Massachusetts Institute of Technology general circulation model. Idealized simulations are used to demonstrate that material parameters can be tuned so that both VP and MEB rheologies lead to similar cohesive stress states, arching behaviour and heterogeneity in the deformation fields. As expected, simulations with MEB rheology generally show more heterogeneity than the VP model as measured by the number of simulated linear kinematic features (LKFs). For both rheologies, the cohesion determines the emergence of LKFs. Introducing gridscale heterogeneity by random model parameter perturbation, however, leads to a larger increase of LKF numbers in the VP simulations than in the MEB simulations and similar heterogeneity between VP and MEB models.
Q1

Impact of internal wave drag on Arctic sea ice
Flocco D., Feltham D., Schroeder D., Aksenov Y., Siahaan A., Tsamados M.
Abstract
A parameterization of the impact of internal waves on momentum transfer at the sea-ice–ocean interface based on previous work by McPhee has been implemented in a sea-ice model for the first time. The ice–ocean drag from internal waves is relevant for shallow mixed layer depth and the presence of a density jump at the pycnocline and is also a function of the strength of the stratification beneath the ocean mixed layer and geometry of the ice interface. We present results from a coupled sea-ice–ocean model where the parameterization of internal wave drag has been implemented. We conducted simulations spanning the years from 2000 to 2017. We find a deceleration of ice drift by 5–8% in both winter and summer, but with significant spatial and temporal variation reaching seasonal average values of ~10%. The spatial variation of ice transport leads to local impacts on deformed ice of magnitude ~0.05 m (2–5%), and reductions in ocean-to-ice heat fluxes of ~1 W m−2, and a decrease in bottom melt of ~0.02–0.04 cm d−1. There is an increase of up to 15% in thickness and ice concentration in the Canadian Arctic and a 10% overall impact on the total sea-ice volume.
Q1

A reassessment of ice cliff dynamics upon debris-covered glaciers
Evatt G.W., Mayer C., Wirbel A., Abrahams I.D., Nicholson L.
Abstract
We present a new model for understanding ice cliff dynamics within a debris-covered glacier ablation zone. This simple energy-balance model incorporates a moving frame of reference, made necessary by the melt of the surrounding debris-covered ice. In so doing, this also formalises how different types of field measurements can be utilised and compared. Our predictions include showing: ice cliffs can endogenously select their own slope angles; that there should be an indifference between illuminated north- and south-facing ice cliff slopes; that ice cliffs grow steeper with thicker debris layers; that ice cliffs cannot stably exist below a certain critical debris thickness and that some modelling of ice cliffs (when not incorporating the moving frame) may incorrectly estimate ice mass losses. All of our results are produced using parametrisations from Baltoro Glacier, Karakoram.
Q1

Deriving iceberg ablation rates using an on-iceberg autonomous phase-sensitive radar (ApRES)
Schild K.M., Vaňková I., Sutherland D.A., Nicholls K.
Abstract
The increase in iceberg discharge into the polar oceans highlights the importance of understanding how quickly icebergs are deteriorating and where the resulting freshwater injection is occurring. Recent advances in quantifying iceberg deterioration through combinations of modeling, remote sensing and direct in situ measurements have successfully calculated overall ablation rates, and surface and sidewall ablation; however, in situ measurements of basal melt rates have been difficult to obtain. Radar has successfully measured iceberg thickness, but repeat measurements, which would capture a change in iceberg thickness with time, have not yet been collected. Here we test the applicability of using an on-iceberg autonomous phase-sensitive radar (ApRES) to quantify basal ablation rates of a large (~800 m long) non-tabular Arctic iceberg during an intensive 2019 summer field campaign in Sermilik Fjord, southeast Greenland. We find that ApRES can be used to measure basal ablation even over a short deployment period (10 d), and also provide a lower bound on sidewall melt. This study fills a critical gap in iceberg research and pushes the limits of field instrumentation.
Q1

On sea ice emission modeling for MOSAiC's L-band radiometric measurements
Hernández-Macià F., Gabarró C., Huntemann M., Naderpour R., Johnson J.T., Jezek K.C.
Abstract
The retrieval of sea ice thickness using L-band passive remote sensing requires robust models for emission from sea ice. In this work, measurements obtained from surface-based radiometers during the MOSAiC expedition are assessed with the Burke, Wilheit and SMRT radiative transfer models. These models encompass distinct methodologies: radiative transfer with/without wave coherence effects, and with/without scattering. Before running these emission models, the sea ice growth is simulated using the Cumulative Freezing Degree Days (CFDD) model to further compute the evolution of the ice structure during each period. Ice coring profiles done near the instruments are used to obtain the initial state of the computation, along with Digital Thermistor Chain (DTC) data to derive the sea ice temperature during the analyzed periods. The results suggest that the coherent approach used in the Wilheit model results in a better agreement with the horizontal polarization of the in situ measured brightness temperature. The Burke and SMRT incoherent models offer a more robust fit for the vertical component. These models are almost equivalent since the scattering considered in SMRT can be safely neglected at this low frequency, but the Burke model misses an important contribution from the snow layer above sea ice. The results also suggest that a more realistic permittivity falls between the spheres and random needles formulations, with potential for refinement, particularly for L-band applications, through future field measurements.
Top-100
Citing journals
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Journal of Nutritional Science and Vitaminology
132 citations, 3.83%
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Nippon Shokuhin Kagaku Kogaku Kaishi
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69 citations, 2%
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Citing publishers
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Japan Society for Food Engineering
4 citations, 0.12%
|
|
SciELO
4 citations, 0.12%
|
|
Japan Epidemiological Association
4 citations, 0.12%
|
|
Trans Tech Publications
3 citations, 0.09%
|
|
American Physiological Society
3 citations, 0.09%
|
|
Korean Society of Industrial Engineering Chemistry
3 citations, 0.09%
|
|
Crop Science Society of Japan
3 citations, 0.09%
|
|
3 citations, 0.09%
|
|
Korean Society for Food Science of Animal Resources
3 citations, 0.09%
|
|
Institute of Electrical and Electronics Engineers (IEEE)
3 citations, 0.09%
|
|
Science Alert
3 citations, 0.09%
|
|
Japan Society for Occupational Health
3 citations, 0.09%
|
|
The Plant Resources Society of Korea
3 citations, 0.09%
|
|
The Society for Free Radical Research Japan
3 citations, 0.09%
|
|
World Scientific
2 citations, 0.06%
|
|
Pleiades Publishing
2 citations, 0.06%
|
|
Georg Thieme Verlag KG
2 citations, 0.06%
|
|
King Saud University
2 citations, 0.06%
|
|
Kyushu University
2 citations, 0.06%
|
|
Society of Chemical Engineers, Japan
2 citations, 0.06%
|
|
IOP Publishing
2 citations, 0.06%
|
|
American Society for Biochemistry and Molecular Biology
2 citations, 0.06%
|
|
Brazilian Society of Chemical Engineering
2 citations, 0.06%
|
|
The Korean Society of Community Nutrition
2 citations, 0.06%
|
|
2 citations, 0.06%
|
|
Biomedical Research Foundation
2 citations, 0.06%
|
|
Japanese Society for Hygiene
2 citations, 0.06%
|
|
Society of Powder Technology
2 citations, 0.06%
|
|
Institute of Organic Chemistry & Biochemistry
2 citations, 0.06%
|
|
Annual Reviews
2 citations, 0.06%
|
|
BMJ
2 citations, 0.06%
|
|
Brewing Society of Japan
2 citations, 0.06%
|
|
Japanese Society of Animal Science
2 citations, 0.06%
|
|
Japan Ergonomics Society
2 citations, 0.06%
|
|
Japan Association on Odor Environment
2 citations, 0.06%
|
|
Society for Hard Tissue Regenerative Biology
2 citations, 0.06%
|
|
IOS Press
1 citation, 0.03%
|
|
1 citation, 0.03%
|
|
American Association for the Advancement of Science (AAAS)
1 citation, 0.03%
|
|
AIP Publishing
1 citation, 0.03%
|
|
American Diabetes Association
1 citation, 0.03%
|
|
1 citation, 0.03%
|
|
HACCP Consulting
1 citation, 0.03%
|
|
Show all (70 more) | |
100
200
300
400
500
600
700
|
Publishing organizations
10
20
30
40
50
60
70
|
|
University of Tokyo
61 publications, 3.71%
|
|
Tokyo University of Agriculture
53 publications, 3.22%
|
|
Kyoto University
47 publications, 2.86%
|
|
Osaka Metropolitan University
28 publications, 1.7%
|
|
Kyushu University
27 publications, 1.64%
|
|
Kobe Gakuin University
26 publications, 1.58%
|
|
Chiba University
21 publications, 1.28%
|
|
Tohoku University
20 publications, 1.22%
|
|
Ochanomizu University
19 publications, 1.16%
|
|
Ehime University
17 publications, 1.03%
|
|
Mukogawa Women's University
17 publications, 1.03%
|
|
Kagawa University
15 publications, 0.91%
|
|
Kagawa Nutrition University
15 publications, 0.91%
|
|
Koshien University
15 publications, 0.91%
|
|
University of Tsukuba
14 publications, 0.85%
|
|
Nagoya University
14 publications, 0.85%
|
|
Nihon University
14 publications, 0.85%
|
|
University of Nis
14 publications, 0.85%
|
|
École de Technologie Supérieure
11 publications, 0.67%
|
|
Shizuoka University
10 publications, 0.61%
|
|
Kumamoto University
9 publications, 0.55%
|
|
Gifu University
9 publications, 0.55%
|
|
University of Shizuoka
9 publications, 0.55%
|
|
Hokkaido University
8 publications, 0.49%
|
|
RIKEN-Institute of Physical and Chemical Research
8 publications, 0.49%
|
|
Hiroshima University
8 publications, 0.49%
|
|
Tokyo Kasei University
8 publications, 0.49%
|
|
Kobe University
7 publications, 0.43%
|
|
Hyogo Medical University
7 publications, 0.43%
|
|
Yamagata University
7 publications, 0.43%
|
|
Kyoto Prefectural University
7 publications, 0.43%
|
|
University of the Ryukyus
7 publications, 0.43%
|
|
Utsunomiya University
7 publications, 0.43%
|
|
University of Shiga Prefecture
7 publications, 0.43%
|
|
Tokyo Women's Medical University
6 publications, 0.36%
|
|
Okayama University
6 publications, 0.36%
|
|
University of Miyazaki
6 publications, 0.36%
|
|
Kansai Medical University
6 publications, 0.36%
|
|
University of Hyogo
6 publications, 0.36%
|
|
Osaka University
5 publications, 0.3%
|
|
Tokushima University
5 publications, 0.3%
|
|
Nippon Medical School
5 publications, 0.3%
|
|
Kyorin University
5 publications, 0.3%
|
|
Tokushima Bunri University
5 publications, 0.3%
|
|
Nara Women's University
5 publications, 0.3%
|
|
Kobe Women's University
5 publications, 0.3%
|
|
Keio University
4 publications, 0.24%
|
|
Osaka Medical and Pharmaceutical University
4 publications, 0.24%
|
|
Tokai University
4 publications, 0.24%
|
|
National Center for Geriatrics and Gerontology
4 publications, 0.24%
|
|
Shinshu University
4 publications, 0.24%
|
|
Josai University
4 publications, 0.24%
|
|
Ritsumeikan University
4 publications, 0.24%
|
|
Kagoshima University
4 publications, 0.24%
|
|
Mie University
4 publications, 0.24%
|
|
Iwate University
4 publications, 0.24%
|
|
Obihiro University of Agriculture and Veterinary Medicine
4 publications, 0.24%
|
|
Oita University
4 publications, 0.24%
|
|
Tamagawa University
4 publications, 0.24%
|
|
Kanazawa University
3 publications, 0.18%
|
|
Tokyo Metropolitan University
3 publications, 0.18%
|
|
Tokyo Medical and Dental University
3 publications, 0.18%
|
|
Waseda University
3 publications, 0.18%
|
|
Kindai University
3 publications, 0.18%
|
|
Tokyo Metropolitan Institute of Gerontology
3 publications, 0.18%
|
|
Toho University
3 publications, 0.18%
|
|
Nagasaki University
3 publications, 0.18%
|
|
Niigata University
3 publications, 0.18%
|
|
Chubu University
3 publications, 0.18%
|
|
Jikei University School of Medicine
3 publications, 0.18%
|
|
Hirosaki University
3 publications, 0.18%
|
|
Fukuoka University
3 publications, 0.18%
|
|
University of Fukui
3 publications, 0.18%
|
|
Toyo University
3 publications, 0.18%
|
|
University of Kitakyushu
3 publications, 0.18%
|
|
Tokyo Gakugei University
3 publications, 0.18%
|
|
University of Niigata Prefecture
3 publications, 0.18%
|
|
Central Food Technological Research Institute
2 publications, 0.12%
|
|
Tokyo University of Agriculture and Technology
2 publications, 0.12%
|
|
Nagoya University of Arts and Sciences
2 publications, 0.12%
|
|
Osaka University of Health and Sport Sciences
2 publications, 0.12%
|
|
Yokohama National University
2 publications, 0.12%
|
|
National Institute for Environmental Studies
2 publications, 0.12%
|
|
Asahikawa Medical University
2 publications, 0.12%
|
|
Hokkaido Information University
2 publications, 0.12%
|
|
Juntendo University
2 publications, 0.12%
|
|
Nagoya City University
2 publications, 0.12%
|
|
Kyoto Prefectural University of Medicine
2 publications, 0.12%
|
|
Teikyo University
2 publications, 0.12%
|
|
University of Toyama
2 publications, 0.12%
|
|
Yamaguchi University
2 publications, 0.12%
|
|
National Defense Medical College
2 publications, 0.12%
|
|
Ryukoku University
2 publications, 0.12%
|
|
Seikei University
2 publications, 0.12%
|
|
Wakayama University
2 publications, 0.12%
|
|
Örebro University Hospital
1 publication, 0.06%
|
|
Massachusetts Institute of Technology
1 publication, 0.06%
|
|
National Institutes for Quantum Science and Technology
1 publication, 0.06%
|
|
University of Tsukuba Hospital
1 publication, 0.06%
|
|
Harbin Medical University
1 publication, 0.06%
|
|
Show all (70 more) | |
10
20
30
40
50
60
70
|
Publishing organizations in 5 years
1
2
3
4
5
6
7
8
|
|
Tokyo University of Agriculture
8 publications, 7.34%
|
|
Nagoya University
6 publications, 5.5%
|
|
Kyoto University
5 publications, 4.59%
|
|
University of Tokyo
5 publications, 4.59%
|
|
Osaka Metropolitan University
4 publications, 3.67%
|
|
Kagawa Nutrition University
4 publications, 3.67%
|
|
Tohoku University
3 publications, 2.75%
|
|
Ritsumeikan University
3 publications, 2.75%
|
|
Tokushima University
3 publications, 2.75%
|
|
Chubu University
3 publications, 2.75%
|
|
University of Shizuoka
3 publications, 2.75%
|
|
Jikei University School of Medicine
3 publications, 2.75%
|
|
Kyoto Prefectural University
3 publications, 2.75%
|
|
Kobe Gakuin University
3 publications, 2.75%
|
|
Central Food Technological Research Institute
2 publications, 1.83%
|
|
Tokyo Medical and Dental University
2 publications, 1.83%
|
|
Kyushu University
2 publications, 1.83%
|
|
Josai University
2 publications, 1.83%
|
|
Ochanomizu University
2 publications, 1.83%
|
|
Obihiro University of Agriculture and Veterinary Medicine
2 publications, 1.83%
|
|
Toyo University
2 publications, 1.83%
|
|
Shizuoka University
2 publications, 1.83%
|
|
Örebro University Hospital
1 publication, 0.92%
|
|
Tokyo Metropolitan University
1 publication, 0.92%
|
|
Keio University
1 publication, 0.92%
|
|
Nagoya University of Arts and Sciences
1 publication, 0.92%
|
|
Osaka University
1 publication, 0.92%
|
|
Japan Science and Technology Agency
1 publication, 0.92%
|
|
Kobe University
1 publication, 0.92%
|
|
Tokai University
1 publication, 0.92%
|
|
Hokkaido Information University
1 publication, 0.92%
|
|
Hokkaido Bunkyo University
1 publication, 0.92%
|
|
Hokkaido University
1 publication, 0.92%
|
|
Juntendo University
1 publication, 0.92%
|
|
National Center for Geriatrics and Gerontology
1 publication, 0.92%
|
|
University of Tokyo Hospital
1 publication, 0.92%
|
|
Kindai University
1 publication, 0.92%
|
|
Nihon University
1 publication, 0.92%
|
|
Tokyo Metropolitan Institute of Gerontology
1 publication, 0.92%
|
|
National Center For Child Health and Development
1 publication, 0.92%
|
|
Nippon Medical School
1 publication, 0.92%
|
|
National Institute for Physiological Sciences
1 publication, 0.92%
|
|
Gifu University
1 publication, 0.92%
|
|
Saitama Medical University
1 publication, 0.92%
|
|
Kagawa University
1 publication, 0.92%
|
|
Yamaguchi University
1 publication, 0.92%
|
|
Ehime University
1 publication, 0.92%
|
|
Wakayama Medical University
1 publication, 0.92%
|
|
International University of Health and Welfare
1 publication, 0.92%
|
|
Shimane University
1 publication, 0.92%
|
|
Meijo University
1 publication, 0.92%
|
|
Iwate University
1 publication, 0.92%
|
|
Kyoto Sangyo University
1 publication, 0.92%
|
|
University of the Ryukyus
1 publication, 0.92%
|
|
National Defense Medical College
1 publication, 0.92%
|
|
Utsunomiya University
1 publication, 0.92%
|
|
Oita University
1 publication, 0.92%
|
|
University of Shiga Prefecture
1 publication, 0.92%
|
|
University of Hyogo
1 publication, 0.92%
|
|
Setsunan University
1 publication, 0.92%
|
|
Shizuoka General Hospital
1 publication, 0.92%
|
|
Ryukoku University
1 publication, 0.92%
|
|
Kanagawa Institute of Technology
1 publication, 0.92%
|
|
University of Niigata Prefecture
1 publication, 0.92%
|
|
Nippon Sport Science University
1 publication, 0.92%
|
|
Tokoha University
1 publication, 0.92%
|
|
Konan Women's University
1 publication, 0.92%
|
|
French Institute of Health and Medical Research
1 publication, 0.92%
|
|
Show all (38 more) | |
1
2
3
4
5
6
7
8
|
Publishing countries
20
40
60
80
100
120
140
160
180
|
|
Japan
|
Japan, 165, 10.04%
Japan
165 publications, 10.04%
|
USA
|
USA, 2, 0.12%
USA
2 publications, 0.12%
|
China
|
China, 1, 0.06%
China
1 publication, 0.06%
|
Switzerland
|
Switzerland, 1, 0.06%
Switzerland
1 publication, 0.06%
|
20
40
60
80
100
120
140
160
180
|
Publishing countries in 5 years
10
20
30
40
50
60
|
|
Japan
|
Japan, 58, 53.21%
Japan
58 publications, 53.21%
|
USA
|
USA, 1, 0.92%
USA
1 publication, 0.92%
|
Switzerland
|
Switzerland, 1, 0.92%
Switzerland
1 publication, 0.92%
|
10
20
30
40
50
60
|