dataesr/scientific-paragraphs-categorization huggingface dataset:
Therefore, the blackbody correction is overall larger for type 2 clouds than for type 1 ones (Fig. 3a ). As a result, a better agreement between τ vis / τ a from type 1 (dotted lines) and from type 2 (dashed) clouds is clearly noted after correction (Fig. 5b ) than before correction (Fig. 5a ) for the largest 2τ a between 1 and 1. 5. After correction, the overall difference between τ vis / τ a from type 2 and from type 1 clouds is +1 to +5 % at 2τ a = 0. 7, which is possibly due to additional biases of -0. 2 to -0. 8 K (Fig. 1 ) in the computed R BG , even though actual differences of the τ vis / τ a ratios cannot be ruled out because two distinct ensembles of clouds are compared. Further analyses of the differences between observations and computations are being conducted to help inform and improve future versions of the IIR science data products.
Acknowledgements. The authors thank  Steve Platnick  and  Bob Holz  for many fruitful discussions about active and passive remote sensing retrievals and thank  Ping Yang  for providing the ice crystal optical properties used in our simulation studies. The authors are grateful to the  ICARE data center in France  for their help with the development of the IIR Level 2 algorithm. CALIPSO products are publicly available at the Atmospheric Science Data Center of the  NASA Langley Research Center  and at  ICARE data center. The authors are thankful to  Patricia Lucker  for her support, to CNES, and to  CNRS  ( Centre National de la Recherche Scientifique ). Edited by:  V. Amiridis.
The Advent of Fox News: A Natural Experiment To evaluate empirically our predictions shown in Figure  1 , we draw on the sample of cable markets constructed by  DellaVigna and Kaplan (2007) , which records the geographic expansion of Fox News Channel across the country between 1998 and 2002. The data are at the town level. We aggregate these data to the congressional district level, creating two types of districts: those without Fox News and those in which at least some portion of the district had access to Fox News. We follow previous researchers  (Clinton and Enamorado 2014; DellaVigna and Kaplan 2007; Hopkins and Ladd 2014 ) in treating the patchy rollout of Fox News Channel as a natural experiment. The introduction of Fox News creates exogenous variation in the partisan composition of national news media across congressional districts.
Because we aggregate the town-level data to the congressional district level, we take the added precaution of assessing whether imbalances exist between districts with and without Fox News on covariates that correlate with congressional voting behavior. The results are displayed in Table  1  for the full sample and separated by Democratic and Republican districts. It does not appear that the rollout of Fox News is correlated with the party of congressional members, their ideology, seniority, campaign spending behavior, the quality of challengers, the viability of incumbents, or the districts' presidential vote (these measures are described in greater detail in Section 2 of the Supporting Information). The one exception is the seniority of Republican members of Congress. Fox News entered districts in which Republicans had approximately 1.
We test whether Fox News influences members' dynamic partisanship by interacting the polynomial terms with an indicator variable for the presence of Fox News in the district. 5 Finally, we estimate the empirical model separately for Republicans and Democrats in order to test our expectation that Fox News caused Republican members to become more partisan as elections approached, while causing Democrats to become less partisan. 6   Pr(Party Support i,v = 1) = log it -1 ⎛ ⎝ ␣ + 3 k=1 k Days To Election k v + Fox News i + 3 k=1 ␦ k Days To Election k v × Fox News i + ␤x i + ␥z v ⎞ ⎠ (1) We include all party votes during the period of analysis (N = 1, 565), coding party support as 1 and defection as 0. 7 DaysToElection measures the number of days between each vote v and Election Day. 8  We use DellaVigna and  Kaplan's (2007)  data to identify districts with Fox News and the timing of Fox News's entry into the district.
9 Conceptualizing the presence of Fox News in each congressional district as a dichotomy is an admittedly coarse approach. After all, the underlying data were collected at the town level and drawn from a sample of cable markets. 10 Therefore, using a dichotomous measure of Fox News in districts surely overlooks variation in the penetration of Fox News across districts. Moreover, there is a small (but positive) probability that we falsely classify a district as not having Fox News, since it is possible that a town within the district has Fox News but does not appear in the sample. Fortunately, these sources of error are functionally equivalent to treating the control group, furnishing a conservative test of our theoretical predictions by 6 This approach permits a different magnitude of effect across Democrats and Republicans.
Conversely, in their empirical model,  Clinton and Enamorado (2014)  assume the effect of Fox News is symmetric across Democrats and Republicans in Congress (given the absence of an interaction between the presence of Fox News and party) and uniform over the election cycle. 7 We use the roll-call data made available on Keith Poole's Voteview website (http://voteview. com/) and code absences and other unrecorded activity as missing values. Eleven party votes that occurred in the lame duck session following the 2002 elections were removed from the analysis since we do not examine the subsequent election cycle. biasing against finding differences between Fox News and non-Fox News members. As a robustness check, we later measure the district-level penetration of Fox News as the proportion of cable subscribers in the district with access to the channel and arrive at substantively identical results to those using the dichotomous measure.
In this and subsequent simulations, all other control variables are held constant at their mean. These simulations are conducted using code written by the authors that implements the algorithms detailed in  King, Tomz, and Wittenberg (2000). This code is available upon request. confidence intervals, 83. 5% confidence intervals are appropriate for achieving a Type I error rate of 5% (i. e. , 95% confidence;  Goldstein and Healy 1995; Maghsoodloo and Huang 2010). As predicted, there is a general pattern of decreasing party support over the election cycle among non-Fox News members-Democrats and Republicans alike. We also observe divergence in the predicted probabilities of party support between non-Fox News and Fox News members when elections approach, but not during periods of the election cycle when elections are distant.
S. House of Representatives. To the contrary, Fox News shifted both Democratic and Republican members towards the Republican Party. If anything, Fox News may be responsible for a rightward shift in politics at the elite level  (Hacker and Pierson 2005). That said, our data do not speak to the later emergence of left-leaning news channels, such as MSNBC. Perhaps, the emergence of a liberal counterweight to Fox News induced Democrats to move leftward. If this is the case, the combination of left-and right-leaning news channels may promote party polarization in Congress. We leave this question to future research. We also leave to future studies the matter of whether the introduction of Fox News had significant effects on legislative elections. Hopkins and Ladd (2014)  find that Fox News increased turnout among Republicans in presidential elections.
The measurement of the absolute neutrino mass scale remains the greatest challenge for both disciplines. However, while particle physics experiments are capable of determining two of the squared mass differences, along with the number of active neutrino families, their mixing angles, and one of the complex phases  [8] , a combination of cosmological datasets allows one to place more competitive upper limits on the total neutrino mass (summed over the three families) as opposed to beta-decay experiments  [9] [10] [11] [12] [13] [14] [15]. The knowledge of the total mass and type of hierarchy will complete the understanding of the neutrino sector, and shed light into several critical issues in particle physics -such as leptogenesis or baryogenesis. A variety of cosmological probes and complementary techniques can be used to study massive neutrinos, and to obtain stringent constraints on their total mass.
This has been possible thanks to extensive data provided by the Sloan Digital Sky Survey (SDSS)  [26] , which has dramatically increased the statistical power of the forest. Several studies in the literature have exploited the Lyα forest constraining power, mainly due to independent systematics and contrasting directions of degeneracy in parameter space  [9, 10, [27] [28] [29] [30] [31] [32] [33] [34] [35] ; the synergy with distinct datasets has contributed to obtain competitive upper bounds of the total neutrino mass  [10] [11] [12] [13] [14] [15]. Cosmological measurements are also capable of constraining the properties of relic neutrinos, and possibly of other light relic particles  [2] [3] [4] 7]. In particular, the density of radiation ρ R in the Universe (which includes photons and additional species) is usually parameterized by the effective number of neutrino species N eff , and the neutrino contribution to the total radiation content is expressed in terms of N eff via the relation ρ R = ρ γ + ρ ν = 1 + 7 8 4 11 4/3 N eff ρ γ , (1) where ρ γ and ρ ν are the energy density of photons and neutrinos, respectively  [3].
The paper is organized as follows. In Section II, we describe the various datasets adopted in this work with a particular emphasis on the Lyα forest sample. In Section III, we briefly illustrate our suite of hydrodynamical simulations with massive neutrinos used in the study, and explain how neutrinos are numerically implemented. In Section IV, we outline our general technique to construct the global likelihood and obtain joint constraints on cosmological parameters; we also present our analytic approximation for the Lyα likelihood to account for nonstandard dark radiation scenarios, test the accuracy of the approximation in the linear regime, and explain in detail our analysis methodology -i. e. , frequentist versus Bayesian approach. Joint constraints on N eff and m ν are presented in Section V, where we also test the validity of our approximation in the nonlinear regime via cosmological hydrodynamical simulations with nonstandard N eff values.
II. DATASETS The joint constraints on N eff and m ν presented in this work are obtained from a combination of LSS and CMB measurements. As LSS probes, we used the one-dimensional Lyα forest flux power spectrum derived from the Data Release 9 (DR9) of the Baryon Acoustic Spectroscopic Survey (BOSS  [26, 46] ) quasar data  [35] , combined with the measurement of the BAO scale in the clustering of galaxies from the BOSS Data Release 11 (DR11)  [47]. BOSS  [46]  is the cosmological counterpart of the third generation of the SDSS, the leading ground-based astronomical survey designed to explore the large-scale distribution of galaxies and quasars by using a dedicated 2. 5m telescope at Apache Point Observatory  [26]. Specifically for the Lyα forest, our data consist of 13 821 quasar spectra, carefully selected according to their high quality, signal-tonoise ratio and spectral resolution, to bring systematic uncertainties at the same level of the statistical uncertainties.
The Lyα forest flux power spectrum is measured in twelve redshifts bins, from z = 2. 2 to 4. 4, in intervals of ∆z = 0. 2, and spans thirty-five wave numbers in the k range [0. 001 -0. 02], with k expressed in (km/s) -1 , which corresponds approximately to [0. 1 -2] (Mpc/h) -1 at z ∼ 3. Correlations between different redshift bins were neglected, and the Lyα forest region was divided into up to three distinct z-sectors to minimize their impact. Noise, spectrograph resolution, metal contaminations and other systematic uncertainties were carefully subtracted out or accounted for in the modeling  [35]. As CMB probes, we adopted a combination of datasets collectively termed 'CMB', which includes Planck (2013) temperature data from the March 2013 public release (both high-ℓ and low-ℓ)  [48] , the high-ℓ public likelihoods from the Atacama Cosmology Telescope (ACT)  [49]  and the South Pole Telescope (SPT)  [50]  experiments, and some low-ℓ WMAP polarization data  [51].
III. SIMULATIONS To constrain neutrino masses and possible extrarelativistic degrees of freedom exploiting Lyα forest information, a detailed modeling of the line-of-sight power spectrum of the Lyα transmitted flux is required. This is because the scales probed lie fully in the non-linear regime, and therefore non-linear simulations are necessary to compare to the Lyα one-dimensional flux power spectra (while the BAO peak scale is not relevant here). To this end, we devised a novel suite of hydrodynamical cosmological simulations which include massive neutrinos  [52]  to map the parameter space around the central reference model on a regularly-spaced grid, and compute first and second-order derivatives in the Taylor expansion of the Lyα forest flux. We use those simulations here in combination with the previously described datasets to obtain bounds on N eff and m ν , together with an analytic approximation to include non-standard dark radiation scenarios in the Lyα likelihood.
In detail, for a model M defined by three categories of parameters -cosmological (α), astrophysical (β), nuisance (γ) -globally indicated with the multidimensional vector Θ = (α, β, γ), and for a N k × N z dataset X of power spectra P (k i , z j ) measured in N k bins in k and N z bins in redshift with experimental Gaussian errors σ i,j , with σ = {σ i,j }, i = 1, N k and j = 1, N z , the Lyα likelihood is written as: L Lyα (X, σ|Θ) = exp[-(∆ T C -1 ∆)/2] (2π) N k Nz 2 |C| L Lyα prior (γ) (3) where ∆ is a N k × N z matrix with elements ∆(k i , z j ) = P (k i , z j ) -P th (k i , z j ), P th (k i , z j ) is the predicted theoretical value of the power spectrum for the bin k i and redshift z j given the parameters (α, β) and computed from simulations  [52] , C is the sum of the data and simulation covariance matrices, and L Lyα prior (γ) accounts for the nuisance parameters, a subset of the parameters Θ.
Specifically, we obtain N eff = 2. 91 +0. 21  -0. 22 (95% CL) and m ν < 0. 15 eV (95% CL) in the first case, and N eff = 2. 88 ± 0. 20 (95% CL) and m ν < 0. 14 eV (95% CL) in the second. Table  I  reports the final results of the fits for all the main cosmological parameters (α), in addition to N eff and m ν , for the two combinations of datasets considered (i. e. , CMB+Lyα or CMB+Lyα+BAO). In particular, our tight constraints on N eff exclude the possibility of a sterile neutrino thermalized with active neutrinosor more generally of any decoupled relativistic relic with ∆N eff ≃ 1 -at significance of over 5 σ, the strongest bound to date, and are fully consistent with the latest constraints recently reported by Planck (2015)  [18]. We discuss the major implications of these results in cosmology and particle physics next.
For example, we tested this by completely removing the dependence on N eff in L Lyα , and found that our final limits on N eff varied only marginally -confirming that most of the constraining power on the number of effective neutrino species indeed resides in the CMB, although some additional -albeit small -information is also contained in the Lyα forest. Therefore, we would expect that the combination of CMB+Lyα will always perform better than the CMB alone, and if combined with the new Planck (2015) data  [74]  the results presented here will be even tighter. In essence, the key is the synergy of the CMB with a high-redshift tracer having different systematics and probing different directions in parameter space. We also note that there is no significant correlation between N eff and m ν in the CMB+Lyα contours (essentially because the CMB is driving the constraints particularly on N eff , and as previously mentioned from CMB measurements alone these two parameters do not show significant correlations), and therefore our upper limits on the total neutrino mass obtained from a joint analysis are consistent with  [13].
ACKNOWLEDGMENTS This work is supported by the  National Research Foundation of Korea (NRF)  through  NRF-SGER 2014055950  funded by the  Korea government (MEST) , and by the faculty research fund of Sejong University in 2014. Some numerical simulations developed for this study were performed using the  Korea Institute of Science and Technology Information (KISTI) supercomputer (Tachyon-I)  under allocation  KSC-2014-C1-045. We also acknowledge  PRACE  for awarding us access to resource Curiethin nodes based in France at TGCC. N. P. -D. and Ch. Y. acknowledge support from grant  ANR-11-JS04-011-01  of  Agence Nationale de la Recherche.
62 m  (Dashora et al. , 2007). Corona images are known to contain significant geometric distortions due to cross-path panoramic scanning. The Frame Ephemeris Camera and Orbital Data camera/spacecraft parameters (roll, pitch, yaw, speed, altitude, azimuth, sun angle and film scanning rate) for Corona missions, needed to construct a camera model and to correct these distortions, are not easily available. To orthorectify the scenes, we defined a non-metric camera model in ERDAS Leica Photogrammetric Suite (LPS), with focal length, air photo scale and flight altitude extracted from the declassified documentation of the KH4 mission  (Dashora et al. , 2007). We used the bundle block adjustment procedure in LPS to simultaneously estimate the orientation of all the CORONA stripes on the basis of 117 ground control points (GCPs).
Latitude and longitude (x, y) information (of the GCPs) were extracted from the panchromatic band of the 2000 Landsat ETM+ image (15 m spatial resolution) on nonglacierized terrain including moraines, river crossings and outwash areas, whereas elevation information (z) were extracted from the SRTM DEM v. 4  (CGIAR-CSI 2004). www. the-cryosphere. net/9/505/2015/ The Cryosphere, 9, 505-523, 2015 A trend analysis on the horizontal shifts between Corona and the reference Landsat scene showed that the largest errors occurred towards the edges of the images, mostly outside the glaciers, and did not impact the area change analysis. 2. The orthorectified Landsat ETM+ scene from December 2000, obtained from the USGS Eros Data Center, was the main data set for the updated glacier inventory. In addition, six orthorectified ASTER products  (2000) (2001) (2002)  were obtained at no cost through the Global Land Ice Monitoring from Space (GLIMS) project  (Raup et al.
These scenes, covering an area of 1107 km 2 were well contrasted and mostly snow-free outside the glaciers. We orthorectified these scenes in ERDAS Imagine Leica Photogrammetry Suite (LPS) using rational polynomial coefficients (RPCs) provided by Digital Globe and the SRTM DEM and mosaicked them in ERDAS Imagine. The scenes were resampled to 3 m pixel size during the orthorectification process using the cubic convolution method suitable for continuous raster data in order to reduce disk space and processing time. One WV2 panchromatic, ortho-ready scene at 50 cm spatial resolution from 2 December 2010 was also obtained to cover the terminus of Zemu glacier, which was missing from the QB extent. All data sets were registered to UTM projection zone 45N, with elevations referenced to the WGS84 datum.
Elevation data sets Two elevation data sets were used in this study: 1. The hydrologically sound, void-filled CGIAR SRTM DEM (90 m spatial resolution) (CGIAR-CSI, 2004) was used to extract glacier parameters for 2000. The SRTM data set is known to have biases on steep slopes and at higher elevations  (Fujita et al. , 2008; Berthier et al. , 2006; Nuth and Kääb, 2011) , as well as due to radar penetration on snow  (Gardelle et al. , 2012b). For this area, the vertical accuracy of the SRTM DEM, calculated as root mean square (RMSE z) with respect to 25 field-based GCPs, was 31 m ± 10 m. The GCPs were obtained in the field on non-glacierized terrain including roads and bare land outside the glaciers using a Trimble Geoexplorer XE series. 2. The Swiss topographic map (1 : 150 000 scale), compiled from Survey of India maps from the 1960s and published by the Swiss Foundation for Alpine Research, was used for manual corrections of the 1962 Corona glacier outlines to discard any seasonal snow and to correct shadow areas or bright water bodies that could be misclassified as ice.
We also mapped supraglacial lakes from this high-resolution data based on band ratios along with texture analysis. For all inventories in the Landsat/ASTER domain, ice masses were separated into glaciers on the basis of the SRTM DEM, using hydrologic functions in an algorithm developed by  Manley (2008) , described in  Racoviteanu et al. (2009). Glacier area, terminus elevation, maximum and median elevation, average slope angle and aspect were extracted on a glacier-by-glacier basis using zonal functions on the SRTM DEM. Average glacier thickness and length were calculated from mass turnover principles and ice flow mechanics by  Huss and Farinotti (2012) , based on the approach of  Farinotti (2009). Their method used our glacier outlines and the SRTM DEM to derive thickness estimates iteratively based on Glen's flow law and a shape factor  (Paterson, 1994).
Raup, National Snow and Ice Data Center, personal communication, 2014). 2. Uncertainties due to different digitization of internal rocks (E rocks ) were derived by comparing area changes computed with internal rocks specific to each data set versus "merged" internal rocks from all data sets. The differences in glacier data sets due to rock inconsistencies amounted to ∼ 2 % of the glacier area. To minimize uncertainties in the glacier area change, we merged rock outcrops from each data set and removed them from all the area calculations. The "inactive" bodies of ice above the bergschrund were included as part of the glacier  (Racoviteanu et al. , 2009). For simplicity, we neglected the area change that might be due to exposure of new internal rock due to glacier ice thinning. Total errors in glacier area estimate for each data set (E) were calculated as RMSE of the classification (E classif ) and the internal rocks (E rock ): E = E 2 classif + E 2 rocks.
The GSI (Sangewar and Shukla, 2009) reported 449 glaciers with an area of 706 km 2 for the 1970s based on topographic maps. Our 1962 Corona glacier inventory yields a smaller total glacier area than the one based on the topographic map (84 km 2 , or 11 %)  (Racoviteanu et al. , 2014)  or the GSI inventory based on topographic maps (48. 3 km 2 , or 7 % area)  (Sangewar and Shukla, 2009). We consider that both of these latter mentioned studies overestimated the glacier area in the 1960s, perhaps due to the presence of persistent snow in the source aerial imagery. We consider the Corona 1962 data set to be more reliable than the inventories based on topographic maps, and hence we used this data set as baseline for comparison with the recent imagery. Glacier inventories in Sikkim for the recent decades also point to contradictory patterns.