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The dataset generation failed
Error code: DatasetGenerationError
Exception: KeyError
Message: 'png'
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1748, in _prepare_split_single
for key, record in generator:
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 797, in wrapped
for item in generator(*args, **kwargs):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 126, in _generate_examples
example[field_name] = {"path": example["__key__"] + "." + field_name, "bytes": example[field_name]}
KeyError: 'png'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1524, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1099, in stream_convert_to_parquet
builder._prepare_split(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1627, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1784, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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string | __url__
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image | txt
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b0f7c03fdd304391a0a5799a98531508_3 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 4. Each tissue analyzed exhibited a significant decline in vRNA during ART. When cell-associated vRNA levels during the plateau stage (treated 28–64 days) are compared to those from untreated mice, the reduction in vRNA levels were significant in all tissues (p , 0.001). Reductions in cell-associated vRNA levels are presented as log10 differences in medians. Mann-Whitney tests were used to generate p values. (Closed symbols=no ART; open symbols=ART). |
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b0f7c03fdd304391a0a5799a98531508_4 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 5. 3B3-PE38 targets and systemically depletes vRNA + cells invivo . Beginning on Day 28 after ART initiation 3B3-PE38 was added to the treatment regimen every other day (7 total doses: 4 at 1 m g/25 g followed by 3 at 5 m g/25 g). The ART only control includes mice treated for 28– 64 days. ( A ) Reductions in cell-associated vRNA levels are presented as log10 differences in medians. Mann-Whitney tests were used to generate p values. ( B ) Reductions in cell-associated vRNA levels for all tissues in (A) are graphed alongside data from untreated mice (Wilcoxon rank-sum statistics with repeated measures corrections). ( C ) Quantitative ISH for No ART mice (Fig. 2), ART only mice (Fig. 2) and the ART + 3B3-PE38 group revealed reductions in the total number of HIV RNA producing cells per gram. When no RNA + cells were detected, then the number of RNA producing cells per gram tissue was set to 200 in the graph (Exact log rank tests with repeated measures corrections). |
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b0f7c03fdd304391a0a5799a98531508_5 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 6. The 3B3-PE38 mediated killing of vRNA producing cells leads to a more rapid reduction in vRNA levels versus ART only. The single Lowess curve for all data points in Fig. 3C (closed symbols; solid line) is graphed together with the combined tissue data for ART + 3B3-PE38 (open symbols; dashed line) to reveal the alteration in cell-associated vRNA levels over time due to the immunotoxin. The beginning of the plateau phase of decay (Day 28) is the divergence point. |
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d8d05b3ddd964383998c244ddffdd6bc_0 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 1. Study Area – Maharashtra |
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d8d05b3ddd964383998c244ddffdd6bc_1 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 2. Flowchart of Methodology |
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d8d05b3ddd964383998c244ddffdd6bc_2 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Table 1 . Standard Precipitation |
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d8d05b3ddd964383998c244ddffdd6bc_3 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 3.Graph Showing Number of Drought Occurred in Grid Number 164 (18.83N,76.108E) |
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d8d05b3ddd964383998c244ddffdd6bc_4 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 4.Graph Showing Number of Drought Occurred in Grid Number 166 |
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d8d05b3ddd964383998c244ddffdd6bc_5 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 8.Persistence Severity Graph for the grid 164(18.83N, |
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d8d05b3ddd964383998c244ddffdd6bc_6 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 5.Graph showing persistence of drought in grid 164 (18.83N, 76.108E) |
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d8d05b3ddd964383998c244ddffdd6bc_7 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 6.Graph showing persistence of drought in grid 166(18.83N,76.108) |
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d8d05b3ddd964383998c244ddffdd6bc_8 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 7.Persistence Severity Graph for the grid 166 (18.83N,76.108) |
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d8d05b3ddd964383998c244ddffdd6bc_9 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 9. Interpolated SPI maps of July 2001, April 2009, and July 2002 |
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d8d05b3ddd964383998c244ddffdd6bc_10 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 10 (a).Interpolated EDI maps for the year 2007 and 2002 (b)Interpolated EDI map for the year |
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d8d05b3ddd964383998c244ddffdd6bc_11 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 11.Area under drought as per SPI and EDI for Deccan Plateau |
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d8d05b3ddd964383998c244ddffdd6bc_12 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 12. SPI map of October 2000 was compared with Figure 13.XOR |
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d8d05b3ddd964383998c244ddffdd6bc_13 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 14(a).VCI maps for the year 2002 and 2010 (b)TCI maps for the year 2002 and 2010 (c)VHI maps for the year 2002 and 2010 (d) SASI maps for the year 2002 and |
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d8d05b3ddd964383998c244ddffdd6bc_14 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 15.Area under drought as observed by different indices for year (a) 2002, and (b) |
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72d8d410909a4e11b2603bea5d7c5a17_0 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Table 1. Parameter setting of the functions for the IPMA. |
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72d8d410909a4e11b2603bea5d7c5a17_1 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Table 2. Comparison performance of the IPMA in the ten functions. |
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6d5df8f446d3401588d2ccd3065b76ed_0 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 1. A high-resolution composite MODIS image of the semi- transparent cirrus case that occurred on 25 January 2010 located over north-east Scotland. The latitude and longitude grid is super- imposed on the image showing latitude 58 to 60 ◦ (left side) and longitude − 8 to 0 ◦ (bottom). The composite image was formed by combining the MODIS red, green and blue channels to obtain the closest “true” colour image. The image is from the NERC Satel- lite Receiving Station, Dundee University, Scotland (http://www. |
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6d5df8f446d3401588d2ccd3065b76ed_1 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 2. The ensemble model as a function of ice crystal maximum dimension, D max . The first element of the model is the hexagonal ice column of aspect ratio unity (first top left), followed by the 6- branched bullet rosette (top centre), the 3-monomer hexagonal ice aggregate (top right), 5-monomer ice aggregate (first bottom left), 8-monomer ice aggregate (bottom centre) and the 10-monomer ice aggregate (bottom right). |
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6d5df8f446d3401588d2ccd3065b76ed_2 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 3. The ensemble model area ratio, A r , as a function of ice crystal diameter or D max . The key is shown on the upper right-hand side of the figure. The members of the ensemble model are repre- sented by the filled cyan circles. The in situ observations are from Field et al. (2008) (red lines), where the plus and cross signs rep- resent the lower and upper range of those observations and those ranges have an uncertainty of ± 30%. The blue error bar repre- sents the mean and range of observations taken from McFarquhar et al. (2013) and the purple error bars represent the uncertainty in the observations taken from Heymsfield and Miloshevich |
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6d5df8f446d3401588d2ccd3065b76ed_3 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Table 1. The bulk values of < β ext >, < ω 0 >and (cid:104) g (cid:105) , calculated at the wavelength 0.865µm, for each distortion, assumed to have val- ues of 0, 0.15, 0.25 and 0.4 plus spherical air bubble inclusions (Full). |
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6d5df8f446d3401588d2ccd3065b76ed_4 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 4. (a) The decadal logarithm of the ensemble model nor- malised scattering phase function as a function of scattering an- gle assuming a variety of distortions. The model cases shown are the pristine (black), slightly distorted (red), moderately distorted (dashed blue) and fully distorted with spherical air bubble inclu- sions (dotted purple). (b) The ratio between the distorted and pris- tine ensemble model phase functions as a function of scattering an- gle. Shown here are slight distortion (red), moderate distortion (dot- ted green) and full with spherical air bubble inclusions (dotted blue). The key is shown in each of the |
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6d5df8f446d3401588d2ccd3065b76ed_5 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 5. The scattering coefficient per particle (m − 2 ) as a function of ice crystal maximum dimension, D max . The PSD was generated assuming IWC and in-cloud temperature values of 0.01gm − 3 and − 50 ◦ C, |
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6d5df8f446d3401588d2ccd3065b76ed_6 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 6. The UKV-model-predicted field of the water vapour mix- ing ratio ( Q v ) on 25 January 2010 at 13:00UTC, between latitudes 57.8 and 59.7 ◦ and longitudes − 5.3 and − 1.8 ◦ . The units of Q v are KgKg − 1 . The PARASOL pixels are represented by the open circles and the aircraft track is represented by the solid line, and X marks the location where the aircraft was directly above the cloud at about 13:33:00UTC. |
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6d5df8f446d3401588d2ccd3065b76ed_7 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 7. (a) The lidar-derived cloud volume extinction coefficient as a function of altitude (m) and time in units of hours after mid- night (UTC). The colour bar on the right-hand side of the figure indicates values of the cloud volume extinction coefficient in units of m − 1 , and the solid line represents the aircraft altitude. (b) The lidar-derived cloud optical depth from 300m below the aircraft to the cloud base as a function of UTC time, and the horizontal solid line shown in the figure indicates an optical depth value of |
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6d5df8f446d3401588d2ccd3065b76ed_8 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 8. A comparison between the retrievals, dropsonde measurements, in situ measurements and NWP model predictions of RH i plotted against the pressure (hPa) for two different locations. (a) The pixel located at longitude − 3.84 and latitude 59.14 ◦ and (b) the pixel located at longitude − 3.20 and latitude 57.97 ◦ . In (a) and (b) , the retrievals are represented by the purple and green plus signs, dropsonde measurements are the solid grey line and filled grey circles, the General Eastern hygrometer is the solid green line, and the FWVS hygrometer is the solid red |
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6d5df8f446d3401588d2ccd3065b76ed_9 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 9. The PARASOL estimates of ensemble model randomisations (based on minimised RMSE) and retrievals of optical thickness as a function of latitude and longitude. (a) The estimated ice crystal randomisation, where the indeterminate results are shown by the black squares, the most randomised phase functions (distortion = 0.4 with spherical air bubble inclusions) by the yellow squares, and the pristine phase functions (distortion = 0) by the purple squares; dark- and light-brown squares represent the slightly distorted (distortion = 0.15) and moderately distorted (distortion = 0.25) phase functions, respectively. (b) The PARASOL-retrieved averaged optical thickness, averaged over all scattering angles, where the decadal logarithm of the retrieved optical thickness is shown by the colour bar on the right-hand side of the figure. (c) The same as (a) but with the indeterminate results |
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6d5df8f446d3401588d2ccd3065b76ed_10 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 10. Differences between the directionally averaged (< S >) and directional ( S(θ) ) spherical albedos as a function of scattering angle at two pixel locations. (a) The spherical albedo differences for the pixel located at 59.03 ◦ and longitude − 3.62 ◦ , assuming the pristine ensemble model (dist = 0) (open red circles), the slightly distorted model (dist = 0.15) (open green triangles), the moderately distorted model (dist = 0.25) (open blue diamonds), and the fully randomised model (dist = 0.4 with spherical air bubble inclusions) (open purple pentagons). (b) The same as (a) but for the pixel lo- cated at latitude 59.14 ◦ and longitude − 3.84 ◦ . The zero difference line is shown by the solid bold line, and the RMSE values calculated for each of the models are shown in each of the |
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6d5df8f446d3401588d2ccd3065b76ed_11 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Table 2. The Levene test statistic, W , applied to test homogeneity of variances in spherical albedo differences between two groups of scattering phase function models for each set of pixels. In the table, the two phase function models are represented for each set of pixels by their assumed distortion values, referred to as Model pair; the total number of pixels used in each test is n . The null hypothesis is given by H 0 , which is either rejected or accepted; k is the number of samples; N is the total number of observations in the two samples; and F 0 . 05 ( k , N − k ) is the value of the tabulated upper critical value at the 5% significance level composed of k and N − k degrees of freedom. |
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6d5df8f446d3401588d2ccd3065b76ed_12 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Table 3. Same definitions as Table 2 but with the Levene test statis- tic applied to a group of seven pixels, where the fully randomised model phase function was found to best fit spherical albedo dif- ferences using minimised RMSE values. The model pair tests are between all other scattering phase function models and the fully randomised scattering phase function |
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6d5df8f446d3401588d2ccd3065b76ed_13 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 11. Associating the PARASOL estimations of shape of the scattering phase function at each pixel to the NWP-model-predicted field of RH i . (a) The estimated shape of the scattering phase func- tion; the yellow squares are as previously defined in Fig. 9. The brown squares represent those PARASOL pixels where no phase function model could be assigned, and the blue squares represent those pixels where phase function models assuming distortion val- ues of between 0 and 0.25 could be assigned. (b) The NWP-model- predicted cloud-top RH i field, where the colour bar indicates the range in predicted RH i |
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6d5df8f446d3401588d2ccd3065b76ed_14 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 12. The percent (%) probability of the penetration depth of solar radiation at 0.865µm as a function of distance from the cloud top (km), and cloud optical depth for (a) forward-scattered and (b) backward-scattered solar radiation in the principal plane, respec- tively. The percent probability of penetration is defined as the last position (distance from the cloud top) of the photon before leaving the cloud to reach the sensor. The cloud optical depth colour scale is defined by the key shown on the upper right-hand side of (a) |
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05a6195fde6d47a289ae059b51bed9c9_0 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Table 1. Percent amino acid identity of Ssa |
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05a6195fde6d47a289ae059b51bed9c9_1 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 1. RT-PCR analysis of Hsp70 isoforms expression in Yarrowia lipolytica . Total RNA was isolated from a wild-type Y. lipolytica strain grown to early exponential phase at 28 u C (left panel), followed by one hour shift at 42 u C (middle panel) or left to grow to stationary phase (right panel). The expression of each Hsp70 ortholog was assessed by RT-PCR analysis (using 1, 10 or 100ng of RNA) as described in Materials and Methods using the ACT1 gene as a loading control. |
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05a6195fde6d47a289ae059b51bed9c9_2 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Table 2. Growth rates and prion phenotypes of strains expressing individual Ssa |
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05a6195fde6d47a289ae059b51bed9c9_3 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 2. Growth of S.cerevisiae expressing individual Ssa proteins. G402 strains A1–A8 [ psi 2 ] cells were streaked onto YPAD plates and incubated at the indicated temperature for 2–4 days as indicated. Strains are as indicated on first panel, pattern of strains is the same on each plate. |
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05a6195fde6d47a289ae059b51bed9c9_4 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 3. Thermoresistance properties of strains expressing individual Ssaps. The indicated strains were grown to early exponential phase at 28 u C then shifted at 52 u C. (A, B) Aliquots were periodically removed and cell viability was assessed by plating tenfold serial dilutions onto YPAD plates. (C) The viability of each strain at the 16 min time point was expressed as a fold enrichment over that of A2 which was arbitrarily set to 1. doi:10.1371/journal.pone.0006644.g003 |
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05a6195fde6d47a289ae059b51bed9c9_5 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 4. Influence of Ssa proteins on refolding of luciferase. Cultures of strains expressing a thermolabile luciferase and individual Ssa proteins (indicated at bottom) were shifted from 30 u C to 37 u C for 30 minutes and then to 42 u C for one hour. Luciferase activity, expressed as a fraction of pre-heat shock activity, was measured after allowing cells to recover for 30 minutes at 25 u C. Cychloheximide was added 50 minutes after shifting to 42 u C to prevent synthesis of luciferase during the recovery period. Wild-type and hsp104 D ( D ) strains (with intact SSA1 – 4 genotype) were used as controls. Data are averages 6 standard deviation from at least two cultures for each strain measured in triplicate. |
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05a6195fde6d47a289ae059b51bed9c9_6 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 5. [ PSI + ] prion phenotype of cells expressing different Ssa proteins. (A) Patches of G402 strains A1-A8, as indicated, were grown over night at 30 u on 1/2YPD and then replica-plated onto 1/2YPD plates and SD plates without adenine (–Ade), which were then incubated at the indicated temperatures. Plates at 25 u were incubated three days. Plates at 30 u were incubated two days. At 37 u the 1/2YPD plate was incubated two days and the –Ade plate for three days. The whiter appearance of cells at 37 u for strains A7 and A8 is due to reduced growth, which has not depleted enough adenine from the medium to cause pigment accumulation. (B) Streaks of cells from the same cultures used in (A) were incubated two days at 30 u followed by three days at 25 u . Red colonies in streaks arise from cells that lost [ PSI + ] before forming the colony. Red sectors in pink or white colonies are progeny of cells that lost [ PSI + ] during growth of the colony. In both (A) and (B) all strains are [ PSI + ] except A6 and A7, in which [ PSI + ] is very unstable (see text). [ PSI + ] ( + ) and [ psi 2 ] ( 2 ) variants of wild type strain 779-6A are included for |
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05a6195fde6d47a289ae059b51bed9c9_7 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 7. SDD-AGE analysis of Sup35p polymers in G402 [ PSI + ] cells. After inducing expression of Sup35-GFP fusion protein (NGMC) for 15 hours, log phase cells were harvested and cell lysates were incubated in SDS to dissolve all but the prion polymers. The lysates were then separated on agarose gels and immunoblotted using anti- GFP antibodies. Strain names are indicated at top. Horizontal line at top indicates origin. A1-A4 were processed separately from A5-A8. Wild type 779-6A [ PSI + ] and [ psi 2 ] controls processed independently for each blot show consistency between the blots. The high molecular weight smear represents polymers (P) of NGMC, faster migrating NGMC monomer (M) is at the lower part of the blot. |
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05a6195fde6d47a289ae059b51bed9c9_8 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 6. Strains expressing individual Ssaps do not generate different prion strains. (A) The wild-type 74D-694 [ psi 2 ][ pin 2 ] strain was transformed with crude extracts from the A1 [ PSI + ] and A4 [ PSI + ] strains as described in Materials and Methods. Induced 74D-694 [ PSI + ] colonies were isolated and their prion phenotype assessed on 1/2 YPD plates along with the [ psi 2 ] and [ PSI + ] derivatives of the A1 and A4 strains. For each transformation, three independent [ PSI + ] transformants are shown (their positions are indicated by dashed lines on the right panel) (B) The A1 [ psi 2 ] and A4 [ psi 2 ] strains were transformed with a crude cell extract from the 74D-694 [ PSI + ][ pin 2 ] strain. The prion phenotypes of representative [ PSI + ] transformants were assessed on 1/2 YPD plates and compared to those of the original A1 and A4 strains. For each transformation, three independent [ PSI + ] transformants are shown (their positions are indicated by dashed lines on the right panel). In each case, the plates were incubated for 3 days at 28 u C and 4 days at 23 u C. |
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05a6195fde6d47a289ae059b51bed9c9_9 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 8. Aggregation of Sup35-GFP in vivo. (A) Fluorescent images of cells from cultures used for the SDD-AGE experiments were taken at the same time cells were processed for SDD-AGE. (B) Images of cells from the same cultures after incubation for an additional six days at 25 u in the same medium. Strains A1-A8 are indicated, + and – are wild type 779-6A [ PSI + ] and [ psi 2 ] controls. |
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05a6195fde6d47a289ae059b51bed9c9_10 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 9. [ URE3 ] prion phenotype of cells expressing different Ssa proteins. (A) Patches of 1161 strains A1-A8, as indicated (see Figure 5A), were grown on 1/2YPD and replica-plated onto 1/2YPD and –Ade plates as in Figure 5A. Plates were incubated at the indicated temperature for two days. Cells expressing Ssa6p are unable to propagate [ URE3 ] and are uniformly [ ure-o ]. (B) Streaks of cells from the same cultures used in (A) were incubated two days at 30 u followed by three days at 25 u . Red colonies in streaks arise from cells that lost [ URE3 ] before forming the colony. Red sectors in pink or white colonies are progeny of cells that lost [ URE3 ] during growth of the colony. [ URE3 ] ( + ) and [ ure-o ] (–) variants of wild type strain 1075 are included for comparison. doi:10.1371/journal.pone.0006644.g009 |
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05a6195fde6d47a289ae059b51bed9c9_11 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 10. Efficiency of [ URE3 ] curing by elevated Ydj1p depends on Hsp70 isoform. Cultures of 1161 [ URE3 ] strains A1–A8 (except A6, which cannot propagate [ URE3 ]), as indicated, were split into non-inducing (-Gal) and Ydj1p inducing ( + Gal) conditions and grown to OD 600nm =1–2. Aliquots were diluted to obtain 300–500 cells per plate onto 1/2YPD and the percentage of [ URE3 ] cells remaining, scored as white colonies on the 1/2YPD plates, is shown. Data are averages of at least two experiments, error bars indicate standard deviation. For strains A2 and A5 we saw no loss of the prion among a total of about 1500 colonies. Overexpressing Ydj1p had no noticeable effects on fitness of any of the strains. |
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05a6195fde6d47a289ae059b51bed9c9_12 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 11. CFTR degradation monitored by cycloheximide-chase. The indicated strains, either [ psi 2 ] (triangles) or [ PSI + ] (squares), were grown to early log phase at 28 u C, then cycloheximide was added at a final concentration of 200 m g/mL. Aliquots were taken periodically and total protein extracts were prepared and subjected to SDS-PAGE and immunoblot analysis as described in Materials and Methods. Immunoblots were quantified by PhosphorImager analysis and the amount of CFTR at time zero was set to 100% (representative blots for each strain are shown on Supplemental Figure S2). Error bars represent the standard error of 3 to 6 independent experiments. |
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05a6195fde6d47a289ae059b51bed9c9_13 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure S2 CFTR degradation monitored by cycloheximide- chase. Representative gels for the quantifications shown in Figure 11 (see Material and Methods for details). Immunoblots against the endoplasmic reticulum protein BiP were used as loading controls. Figure S3 Steady-state protein levels in strains expressing individual Ssaps. Total protein extracts were prepared from the indicated strains as described in figure 11 legend (without the addition of cycloheximide). Equal amounts of proteins were analyzed by SDS-PAGE and immunoblotting with antibodies against the indicated proteins. Table S1 Oligonucleotides used in this |
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b2882e8dfb034b2f816b92d926d22abd_0 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 1. Annual- and zonal-mean surface temperature (a) and precipitation (b) in the GHG case (magenta) and LCTC case |
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b2882e8dfb034b2f816b92d926d22abd_1 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 2. Annual-mean climatology in the GHG run (left column) and its change in the LCTC case (right column) of (a, b) surface temperature (shading) and 900hPa wind (arrows), (c, d) precipitation, (e, f) cloud fraction, and (g, h) eddy kinetic energy (shading) and zonal wind at 700hPa (contours; contour intervals 4ms − 1 in g and 2ms − 1 in h |
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b2882e8dfb034b2f816b92d926d22abd_2 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 3. Monthly-mean surface temperature during the warmest month at each grid point in the GHG simulation (a) and its change in the LCTC simulation (b) . (c, d) Same as in (a, b) but for the coldest month. (e) Annual-mean diurnal range in surface temperature, defined as the difference between daily maxima and minima, and (f) its change in the LCTC case. White lines in (c) indicate the 0 ◦ C contour in the GHG case (solid) and the LCTC case |
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b2882e8dfb034b2f816b92d926d22abd_3 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 4. Terms in the global-mean atmospheric energy budget (Eq. 1) for (a) the GHG simulation and (b) change in the LCTC case (LCTC − GHG). The black bars are the atmospheric heating for both |
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b2882e8dfb034b2f816b92d926d22abd_4 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 5. Change in annual-mean surface temperature (shading) and 900hPa wind (arrows) between the GHG run and the fixed-SST simulation with (a) reduced CO 2 , (b) reduced cloud albedo and (c) change is SST pattern, as well as (d) the sum of all |
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b2882e8dfb034b2f816b92d926d22abd_5 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 6. As in Fig. 5 but for annual-mean precipitation. |
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b2882e8dfb034b2f816b92d926d22abd_6 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 7. Change in annual-mean net surface energy flux (shading, defined positive downwards) and 900hPa wind (arrows) between the GHG run and the fixed-SST run with reduced CO 2 |
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fec0755daed7483c9caeb8b2452e2ae9_0 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Fig. 1. The structure of the proposed study |
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fec0755daed7483c9caeb8b2452e2ae9_1 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Theoretical framework Evaluating |
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fec0755daed7483c9caeb8b2452e2ae9_2 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Impact of the exploratory factor group on the profitability of the tourist enterprise in BinhDinh |
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fec0755daed7483c9caeb8b2452e2ae9_3 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | The result of extracted variance analysis of influencing factors group Initial Eigenvalues Com. |
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fec0755daed7483c9caeb8b2452e2ae9_4 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | KMO and Bartlett's Test |
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fec0755daed7483c9caeb8b2452e2ae9_5 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | The result of correlation between influence factors test Kaiser-Meyer-Olkin Measure of Sampling Adequacy. |
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fec0755daed7483c9caeb8b2452e2ae9_6 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Regression analysis of factors affecting ROA Model |
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fec0755daed7483c9caeb8b2452e2ae9_7 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Unstandardized Coefficients |
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fec0755daed7483c9caeb8b2452e2ae9_8 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Regression analysis of factors affecting ROE Unstandardized Model |
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c717ffb92ca44b8a962a6cf25083e318_0 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 1. The variability in understory vegetation at Howard Springs OzFlux site, Northern Territory, Australia. The months from late October to early November are when growth in the understory begins, which continues on through the wet season until the end of March and start of April, when the understory grasses senesce and cure. The understory remains dry throughout the dry season months unless fire removes dry |
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c717ffb92ca44b8a962a6cf25083e318_1 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Table 1. List of instrumentation installed on the ecosystem and understory flux towers at the Howard Springs OzFlux site; where “ u ” is the along wind component, “ v ” is the across wind component and “ w ” is the vertical wind component of wind velocity in 3-dimensional space, K ↓ and L ↓ refer to incoming and K ↑ and L ↑ refer to outgoing shortwave and longwave radiation, respectively. |
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c717ffb92ca44b8a962a6cf25083e318_2 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 2. Co-spectra plot of vertical wind ( w ) against fluxes of car- bon ( w -C), water ( w -H) and energy ( w - T ) for Howard Springs un- derstory tower for the (a) dry season and (b) wet season. Co-spectra are grouped into 50 exponentially spaced frequency bins and repre- sent times from 1200 to 1400, which are averaged over five consec- utive days without rainfall for each season. Table 2. Records of fire activity at the Howard Springs OzFlux site from years 2012 to |
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c717ffb92ca44b8a962a6cf25083e318_3 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 3. Net Ecosystem Productivity (NEP) for savanna ecosystem (23m tower) and understory (5m tower) components at the Howard Springs OzFlux site, Northern Territory, Australia from September 2012 to October 2014. Data shown are daily NEP totals with a 10- day running mean to aid visualisation. Orange arrows represent the timing of fire events (for fire intensity see Table 2). Positive fluxes indicate a net sink of carbon to the savanna whereas negative fluxes are a net source of carbon to the atmosphere. Rainfall is also in- cluded as daily totals. |
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c717ffb92ca44b8a962a6cf25083e318_4 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 4. Respiration ( R ) for savanna ecosystem (23m tower), un- derstory (5m tower) and overstory (difference between 23 and 5m towers) components at the Howard Springs OzFlux site, Northern Territory, Australia from September 2012 to October 2014. Data shown are daily R totals with a 10-day running mean to aid visual- isation. Orange arrows represent the timing of fire events. Positive fluxes indicate a net sink of carbon to the savanna whereas negative fluxes are a net source of carbon to the atmosphere. Rainfall is also included as daily |
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c717ffb92ca44b8a962a6cf25083e318_5 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Table 3. Seasonal sums and annual mean ( ± SE) of net ecosystem productivity (NEP), respiration ( R ) and gross primary productivity (GPP) calculated for the savanna ecosystem, understory and overstory components at the Howard Springs OzFlux site, Northern Territory, Australia. |
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c717ffb92ca44b8a962a6cf25083e318_6 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 5. Gross Primary Productivity (GPP) for savanna ecosys- tem (23m tower), understory (5m tower) and overstory (difference between 23 and 5m towers) components at the Howard Springs OzFlux site, Northern Territory, Australia from September 2012 to October 2014. Data shown are daily GPP totals with a 10-day run- ning mean to aid visualisation. Orange arrows represent the timing of fire events. Positive fluxes indicate a net sink of carbon to the savanna whereas negative fluxes are a net source of carbon to the atmosphere. Rainfall is also included as daily |
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c717ffb92ca44b8a962a6cf25083e318_7 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Table 4. Error estimates for net ecosystem exchange for the ecosystem and understory flux towers at Howard Springs OzFlux site, Northern Territory, Australia. Estimates are given for each year (2012–2014) and are presented as day (D), night (N) and total (T) error estimates in gCm − 2 t − 1 , where t is day, night or year. |
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c717ffb92ca44b8a962a6cf25083e318_8 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 6. Diurnal ( x axis) fingerprint plot of NEE from the savanna (a) ecosystem (23m tower) and (b) understory (5m tower). Measurements shown are for “wet” and “dry” seasons from September 2012 to October 2014 ( y axis) at the Howard Springs OzFlux site, Northern Territory, Australia. Negative NEE represents the uptake of carbon by the savanna, whereas positive NEE represents the loss of carbon from the savanna. |
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c717ffb92ca44b8a962a6cf25083e318_9 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 7. Daily variability in radiation ( F n ) and soil moisture (Sws) at the Howard Springs tropical savanna site, Northern Territory, Australia from September 2012 to October 2014. Mean daily F n is shown with a 10-day running mean (green) to aid in visualisa- tion and daily mean variability in Sws fraction are shown for 10cm (blue), 40cm (orange), 100cm (brown) and 140cm (purple) |
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3218213b882f4cdca56351e996db5824_0 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Table 1. The 11 parameters studied in this paper. Also shown are the default values and the range over which they are varied. ID Name (unit) Description Default Range delt2KF ( ◦ C) Temperature increment at the LCL for KF trigger 0 − 2, 2 cloudrad ( m ) Cloud radius factor in KF 1500 500, 3000 prcpfrac Fraction of available precipitation in KF, fed back to the grid scale 0.5 0, 1 mixlen Linear factor that multiplies the mixing length within the PBL 1.0 0.5, 1.5 sfcflx Linear factor that modifies the surface fluxes 1.0 0.5, 1.5 wfctKF Linear factor for the vertical velocity (grid scale) used by KF trigger 1.0 0.5, 1.5 delt1KF ( ◦ C) Another method to perturb the temperature at the LCL in KF 0 − 2, 2 autocon1 (kgm − 3 s − 1 ) Autoconversion factors for the microphysics 0.001 Autoconversion factors for the microphysics Microphysics slope intercept parameter for rain Microphysics slope intercept parameter for |
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3218213b882f4cdca56351e996db5824_1 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 1. The flowchart highlighting the main components of the methodology. |
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3218213b882f4cdca56351e996db5824_2 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 2. Histogram of p values from the omnibus tests across all days and response |
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3218213b882f4cdca56351e996db5824_3 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 3. Estimated regression coefficients (i.e., the sensitivity of the model parameters) with median precipitation of the clusters as the response, after clustering with DBSCAN with various parameter values. The red symbols are 95% simultaneous |
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3218213b882f4cdca56351e996db5824_4 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 4. Estimated MMR coefficients (i.e., the sensitivity of the model parameters) on three summary measures (minimum, median, maxi- mum) of different cluster features (latitude, longitude, amount of precipitation, and area and orientation of clusters). Eccentricity is not shown (see text). The red symbols are 95% simultaneous CIs. The clustering is done with DBSCAN with (cid:15) = 2 |
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2917149633f04c6c9e8bde7636b223b1_0 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 1 - Skin prick tests |
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2917149633f04c6c9e8bde7636b223b1_1 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Table 1 Results of skin prick |
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a3ec5144b9744cf099d608cb6a27a499_0 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 1. The fragment of the morphological |
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a3ec5144b9744cf099d608cb6a27a499_1 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Figure 2. The fragment of the morphological graph of ODBMS at the middle and lower management |
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a3ec5144b9744cf099d608cb6a27a499_2 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Table 1. Metric spaces of the morphological graphs of ODBMS at the middle and lower management levels Management |
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a3ec5144b9744cf099d608cb6a27a499_3 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Table 2. Types of the organizational structures in the BMS for January 1, 2018 Classification features and types of management organizational structures |
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c0a133ada1a24fc4ae6348150c48215f_0 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Fig 1. Location of study sites in Northwest Costa Rica. Nancite, Cabuyal and Playa Grande serve as nesting groundsfor olive ridley, green and leatherbackturtles respectively. https://doi.org/10.1371/journal.pone.0177256.g001 |
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c0a133ada1a24fc4ae6348150c48215f_1 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | PLOS ONE | https://doi.org/10.1371/journal.pone.0177256 May 18, |
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c0a133ada1a24fc4ae6348150c48215f_2 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Mean ( ± SD) hatching success, mean ( ± SD) temperature (˚C), mean ( ± SD) daily fluctuation in temperature (˚C), mean ( ± SD) seasonal fluctuation in temperature (˚C) and mean ( ± SD) depth in olive ridley, green and leatherback turtle |
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c0a133ada1a24fc4ae6348150c48215f_3 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Table 1. Hatching success and thermal conditions of sea turtle nests in North Pacific Costa Rica. |
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c0a133ada1a24fc4ae6348150c48215f_4 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Table 2. Nesting beaches where we obtained data on nest temperatures and hatching successper season. Information from leatherback, green and olive ridley turtles was collectedat Playa Grande (PG), Cabuyal (CAB) and Nancite (NAN) respectively. Nest temperatures were monitoredwith thermocou- ples and/or |
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c0a133ada1a24fc4ae6348150c48215f_5 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Fig 2. Thermal conditions in olive ridley, green and leatherback turtle clutches versus nest depth. (a) mean ( ± SE) daily fluctuationin temperature (˚C), (b) mean ( ± SE) seasonalfluctuation (˚C) and (c) mean ( ± SE) temperature (˚C) duringdevelopment. Regressionline corresponds to a logarithmic fit. https://doi.org/10.1371/journal.pone.0177256.g002 PLOS ONE | https://doi.org/10.1371/journal.pone.0177256 May 18, |
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c0a133ada1a24fc4ae6348150c48215f_6 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Fig 3. Smooth fits from generalized additive models (GAM) showing additive effect of nest temperature (˚C) on hatching success. (a) olive ridley turtle, (b) green turtle and (c) leatherbackturtle nests. |
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c0a133ada1a24fc4ae6348150c48215f_7 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Fig 4. Mean hatching successand percentage of clutches of each species versus mean temperature (˚C). (a) Mean hatching success of olive ridley, green and leatherbackturtle clutches per mean temperature (˚C) by 1 (˚C) increments and (b) percentageof clutchesper mean temperature (˚C) by 1 (˚C) increments. Regression line in Fig 4a correspondsto a polynomial |
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03fb2142869f406bbd65dd67ff3791d9_0 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Fig. 1. (A) Cascadia margin turbidite canyons, channels and 1999–2002 core locations. Major canyon/channel systems are outlined in blue. Primary core sites shown with yellow rim, all other 1999–2002 cores are grey. Selected earlier UW and OSU cores shown in white. PC, piston core; BC, box core; KC, kasten core; GC, gravity core; TC, trigger core. Trigger cores omitted for clarity. Inset of Effingham Inlet shows collection site of Pacific Geoscience Centre (PGC) collected piston cores. Yellow boxes indicate approximate areas of Fig. 2a and b. Key onshore paleoseismic sites shown. (B) Southern Cascadia continental margin bathymetry and core sites in greater detail. Core symbology as in (A) . The 3.5kHz Chirp profile tracklines are shown. Segments used in Figs. 9 and 10 shown in green, others in orange. Key onshore paleoseismic sites |
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03fb2142869f406bbd65dd67ff3791d9_1 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Fig. 2. (A) Shaded perspective view of Hydrate Ridge west basin (HRWB) on the central Oregon margin. The basin is protected on all sides from terrestrial sediment input by structural sills with heights of ∼ 500m to the north, 1800m to the east, and 1200m in the south. (B) Perspective shaded view of bathymetry of the Rogue Canyon system and apron, southern Oregon margin. Multiple canyon tributary pathways are shaded grey. No topographic expression of a channel leading from the Rogue Canyon is apparent at the resolution of the multi- beam bathymetry. Similarly, the buried Astoria Channel (foreground) has no bathymetric expression at this latitude. The 3.5kHz reflection tracklines shown. Lines shown in Figs. 9 and 10 are indicated in yellow. Inset shows approximate a and b locations with yellow |
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03fb2142869f406bbd65dd67ff3791d9_2 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Fig. 3. CT, visible imagery and physical properties from the Hydrate Ridge and Rogue Apron cores, central-southern Cascadia margin. Data from HR cores 56 PC-TC and Rogue cores 31PC-TC are each summarized with a single composite of piston and trigger cores, all 14 C ages from each site are plotted on the representative core. These two cores are “flattened” (rescaled with event bases and tops aligned) with Rogue core 31PC at true scale. Undated Rogue Apron core TT0909-01JC also shown flattened to 31 PC-TC. Correlation between sites based on stratigraphic methods described in text, 14 C data, Mazama ash and Holocene/Pleistocene boundary datums. Black boxes indicate locations of enhanced images in Fig. 4. Higher confidence shown by heavy lines, lower confidence with dashed lines, lowest confidence with queried dashed lines. The two sites are 250km apart and are isolated from each other. Hydrate Ridge is isolated from terrestrial and shallow water sediment |
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03fb2142869f406bbd65dd67ff3791d9_3 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Fig. 4. Enhanced CT imagery shown for representative thin turbidites in at Hydrate Ridge and Rogue Apron. CT imagery shown in context in Fig. 3. CT density imagery processed to show approximate sand and silt (orange and yellow); fine silt (orange) and hemipelagic mud (blue). Approximate grain size key shown at bottom. Some units show typical structure such as cross bedding (T5a, T9a, upper and middle left panels), while others have largely lost primary structure due to bioturbation (T9d, T10d) (modified after Goldfinger et al., |
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03fb2142869f406bbd65dd67ff3791d9_4 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Fig. 5. (A) Details of events from the surface to T4, Rogue Apron and Klamath Channel, emphasizing small events T2a and T3a. Detailed magnetic susceptibility, gamma density and P wave velocity records and CT imagery reveal fine-grained mud turbidites between T2 and T3, and T3 and T4, which were originally logged as “dark” clay. Lithologic detail is summarized from cores 55KC, 30TC, 31TC, TT0909- 01TC (Rogue), and 34TC (Klamath). Hemipelagic ages and ranges are calculated from the age model using hemipelagic thickness, and sedimentation rates and 14 C. T1 has apparently eroded into T2 in core 30PC (center) but remains distinct in the Kasten core (left) and in 34TC with hemipelagic sediment between them. CT imagery for both 30 and 31TC, and 01TC are shown for comparison, this imagery is “flattened” on major horizons in 30TC. (B) Detail of CT and smear-slide data from core TN0909-01TC. Smear slides taken in a transect across T2a show the lithic content from hemipelagic material consisting of ∼ 30% clay, 5–7% lithics, and ∼ 65% biogenic material. T2a is 50–60% lithic, the thin bioturbated interval of hemipelagic sediment below is 20–30% lithic, and the tail of T3 is 30–70% lithics. The biogenic material in the tail of T2a is rich in heterogeneous patches of glass sponge spicules transported from shallower water. The grain size plot across T2a in M990730TC is shown and “flattened” to the lithology in 01TC in (B) |
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03fb2142869f406bbd65dd67ff3791d9_5 | hf://datasets/Timbrt/SciOL-CI@c789a077852c1ea9cc12cc9e4cb637b4cc7266e0/train/shard_0.tar | Fig. 7. (A) Detailed physical property and CT data from correlated events T5, T5a, T5b, and T5c in a transect from Rogue Apron to the Trinidad Plunge Pool, flattened to regional event T5. This transect shows the southward increase in thickness, density and grain size for regional event T5 and three southern Cascadia beds (T5a–c). (B) A similar transect for events interpreted as T9, T9a, and T9b. Examples are approximately flattened to correlated event T9, shown by heavy red line. These data are shown in context in Fig. 8. Mean grain size shown for cores with sandier turbidites and large contrast between turbidites and hemipelagic. Grain size mode shown for Smith and Klamath apron cores, which have poorly developed channel systems, and reduced average grain size profiles. Mean and mode shown for 34PC for comparison. In these cores, the grain-size variation is commonly dominated by large biogenic forms. Log-transformed grain size data shown in green for 31 PC, which has the finest grain size profile for the Rogue mud turbidites. See Fig. 1 for core locations. Age control, and density and magnetic scales shown in Fig. |
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Scientific Openly-Licensed Publications
This repository contains companion material for the following publication:
Tim Tarsi, Heike Adel, Jan Hendrik Metzen, Dan Zhang, Matteo Finco, Annemarie Friedrich. SciOL and MuLMS-Img: Introducing A Large-Scale Multimodal Scientific Dataset and Models for Image-Text Tasks in the Scientific Domain. WACV 2024.
Please cite this paper if using the dataset, and direct any questions regarding the dataset to Tim Tarsi
Summary
Scientific Openly-Licensed Publications (SciOL) is the largest openly-licensed pre-training corpus for multimodal models in the scientific domain, covering multiple sciences including materials science, physics, and computer science. It consists of over 2.7M scientific scientific publications converted into semi-structured data. SciOL contains over 18 Million figure-caption pairs.
Note: This repository only contains the figures and captions of SciOL. For the textual data see: SciOL-text
Data Format
We provide the data in the webdataset format, e.g., captions in plain text files and group and compress them together with the images. Each tar file contains 1000 images and captions. Corresponding figures and captions have the same filename (excluding extention). We split the data into a train, test and dev set.
Citation
If you use our dataset in your work, please cite our paper:
@InProceedings{Tarsi_2024_WACV,
author = {Tarsi, Tim and Adel, Heike and Metzen, Jan Hendrik and Zhang, Dan and Finco, Matteo and Friedrich, Annemarie},
title = {SciOL and MuLMS-Img: Introducing a Large-Scale Multimodal Scientific Dataset and Models for Image-Text Tasks in the Scientific Domain},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2024},
pages = {4560-4571}
}
License
The SciOL corpus is released under the CC BY 4.0 license.
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