dataesr/scientific-paragraphs-categorization huggingface dataset:
Figure15. Additional candidate integrated line map overlays (contours) over HST H-band (left) and IRAC channel 1 images (middle; grayscale). HST and Spitzer images were obtained from the CANDELS database. The CO line data were taken from the Natural-mosaic or Smoothed-mosaic when the line emission is unresolved/resolved, respectively. Contours are shown in steps of 1σ starting at ±2σ. Right: Line candidate single-pixel/aperture spectra ("histograms"; for unresolved/resolved emission) and Gaussian fits to the line features (red curves). The observed frequency resolution is the same as in Fig. 5. The velocity range used for the overlays is shown by the dashed blue lines.
Therefore, imposing ΔΓ=0. 5 with a broken power-law spectrum may result in inferred Γ 2 and Γ 1 values that differ from their true values and thus complicate direct comparison to the theoretical prediction for the asymptotic value of Γ 2 , which for p∼2-2. 5 corresponds to Γ 2 ∼2-2. 25. We examined the influence that a broad cooling break could have on our results by implementing the smoothly broken power-law (SBPL) spectrum described in  Granot & Sari (2002) , with a fixed sharpness of the break set to s=0. 85. We fit this model to the XRT and LAT data for GRB130427A and obtained consistent pre-and post-break photon indices of Γ BPL1 =1. 54±0. 02 and Γ BPL2 =2. 04±0. 02, respectively, whereas the SBPL model returned Γ BPL1 =1. 56±0. 07 and Γ BPL2 =2. 06±0. 07. We conclude that the large gap in energy between the XRT and LAT data effectively masks the effects of the curvature in the break energy for the SBPL model as long as the spectral break is well within the MeV domain, resulting in asymptotic photon indices in the XRT and LAT energy ranges that are consistent with those obtained using the simpler BPL model.
LAT detections may be preferentially selecting GRBs that occur in low wind-like circumburst density profiles for which the synchrotron cooling break begins near the X-ray regime and does not evolve to lower energies; hence, the afterglow spectrum above the X-ray regime remains spectrally hard for longer periods of time. The inference that LAT-detected bursts may be preferentially occurring in wind-like environments is consistent with an analysis of the multiwavelength observations of both GRB110731A  (Ackermann et al. 2013a ) and GRB130427A  (Kouveliotou et al. 2013). Using data collected by the XRT, LAT, and the Nuclear Spectroscopic Telescope Array (NuS-TAR),  Kouveliotou et al. (2013)  found that a break between the X-ray and gamma-ray regimes best fits the broadband data for GRB130427A at very late times.
The authors speculate that the cooling break in the afterglow spectra of GRB130427A may not have evolved with time and remained between the XRT and LAT energy ranges owing to a circumstellar density profile that is intermediate between ISM and wind-like circumstellar density profiles. Likewise,  Ackermann et al. (2013a)  performed broadband modeling of optical, UVOT, BAT, XRT, and LAT data associated with GRB110731A and found that initially a single power law adequately fit the broadband SED using BAT, GBM, and LAT data. At a later time a spectral break was observed between the XRT and LAT data, which was interpreted as a cooling break evolving from low to high frequencies for a GRB blast wave evolving in a wind-like environment. Although they concluded that an observed break between the optical and X-ray data can be best explained by the presence of a cooling break between the two regimes, the photon index of Γ=1.
77 obtained through our joint spectral fits for this burst suggests that this break lies above the LAT energy range. Again, the differences between the  Ackermann et al. (2013a)  work and this analysis can be likely attributed to the greater sensitivity at low energies of the Pass 8 data used in this work, although we point out that our analysis does not include fits to optical data as were performed by  Ackermann et al. (2013a). A preference for LAT-detected GRBs to occur in low-density wind-like circumstellar environments was also found by  Cenko et al. (2011) , who modeled the broadband spectral and temporal X-ray, optical, and radio afterglow data of four LATdetected GRBs: GRB090323, GRB090328, GRB090902B, and GRB090926A. The authors found that a wind environment best fit the data for all but GRB090902B, for which a constantdensity ISM environment was preferred.
(2013)  and  Wang et al. (2013). Ackermann et al. (2014)  and  Kouveliotou et al. (2013) , on the other hand, both argue that the high-energy light curve and spectra are consistent with a single electron synchrotron spectrum throughout the evolution of the extended emission. Here we draw similar conclusions from the three intervals for which we compared the XRT and LAT data for GRB130427A. The extension of the XRT spectra overpredicts the emission expected in the 0. 1-100 GeV energy range and suggests that a break exists between the two energy ranges. Our joint spectral fit to the first of these three intervals (t 0 ∼300 s post trigger) shows that the broadband SED can be well described by a single electron synchrotron spectrum with a cooling break between the X-ray and gamma-ray regimes, matching the conclusions of  Kouveliotou et al.
Conclusions We have used joint observations by the Swift XRT and the Fermi LAT of GRB afterglows to investigate the nature of long-lived, high-energy emission observed by Fermi LAT. By extrapolating the XRT-derived spectra of Swift-detected GRBs, we compared the expected flux in the 0. 1-100 GeV energy range to the LAT upper limits for the periods in which the burst position was within the LAT FOV. We found that only a small subset of bursts exhibit afterglow emission that could exceed the LAT detection threshold when extrapolated to the 0. 1-100 GeV energy range. Bursts that do result in late-time LAT detections are almost exclusively drawn from afterglows that exhibit emission brighter than  - --F 10 erg cm s XRT 10 2 1 and harder than Γ XRT 2. Joint broadband spectral fits of XRT and LAT data reveal that a majority of LAT nondetections of relatively bright X-ray afterglows can be explained by an afterglow spectrum with a slightly softer photon index when constrained by both the XRT and LAT data, compared to the photon index derived by fits to the XRT data alone.
Late-time LAT detections may be preferentially selecting GRBs that occur in lowdensity wind-like circumburst environments for which the synchrotron cooling break begins near the X-ray regime and does not evolve to lower energies, resulting in an afterglow spectrum above the X-ray regime that remains spectrally hard for longer periods of time, enhancing the detectability of the afterglow in the LAT energy range. We find no evidence of high-energy emission significantly in excess of the flux expected from the spectrum predicted by the electron synchrotron model. In addition, joint spectral fits of contemporaneous XRT and LAT observations of an episode of energetic X-ray flaring in GRB100728A and a significant X-ray plateau in GRB110213A find that the XRT and LAT data are consistent with a single spectral component.
The aim of this paper is to present the activities carried out by NEA Data Bank on checking, processing and verification of JEFF-3. 3T4 covariances. A picture of the completeness and status of the JEFF-3. 3T4 covariances is addressed. The verification of JEFF-3. 3T4 covariances is performed with nuclear data sensitivity tool providing the k eff uncertainty as a function of the contributing nuclide-reaction pairings including cross-reaction covariances. A total number of 4501 ICSBEP benchmarks is used in this analysis. This exercise is also extended to covariance libraries such as JENDL-4. 0 updated files, ENDF/B-VII. 1, SCALE-6. 2rev8 and ENDF/B-VIII. 0b5, allowing comparison of these results with both the experimental criticality benchmark and different methodologies of evaluation.
1 Introduction JEFF-3. 3T4 [1]  is a fully consistent and complete nuclear data library with all data needed and associated covariance information (full covariance information for the main actinides), which can be reliably used for a large spectrum of applications, and which has shown a better performance than JEFF-3. 2 library  [2]. Previous work carried out by NEA Data Bank on checking, processing and verification of earlier JEFF-3. 3 beta releases has been presented in past JEFF meetings  [3, 4]. In this paper, the efforts of NEA Data Bank focused on the latest beta JEFF-3. 3T4 release are presented. A review of NEA tools and databases is described in Section 2. In Section 3, we have performed a comparison of relative standard deviation and correlation matrix with major covariance nuclear data libraries such as ENDF/B-VII.
1  [5] , JENDL-4. 0u1 [6] , SCALE6. 2 [7]  and the recent one CIELO1(ENDF/B-VIII. 0. b5)  [8]. This information gives a good indication of the current status of JEFF-3. 3T4 covariances. A thorough review of the current covariance data files associated with the latest versions of the JENDL-4. 0 updated files (JENDL-4. 0u) and ENDF/B-VII. 1 evaluated data files can be seen in reference  [9]. Checking and processing issues are remarked in Section 4. After some checking tests of ENDF6 format (e. g. consistency between MF2 and MF32, energy ranges, etc. ) and mathematical verification (e. g. positive definite matrix, abnormal values, etc. ) few problems in raw covariances were noted. The complete set of JEFF-3. 3T4 covariances (MF31, MF32/MF33, MF34 and MF35) are processed using the code NJOY2012.
NEA tools and databases The processing and verification of nuclear data covariances have been performed with the NEA tools and databases. These tools and databases are extensively used by the nuclear data community being an essential part of the Nuclear Data Services delivered by the NEA. Hereafter, a brief summary of these tools is presented emphasising the main features on nuclear data covariances: -The java-based nuclear information software (JANIS)  [12]  software developed by the NEA Data Bank is used to facilitate the visualisation and manipulation of nuclear data, giving access to evaluated nuclear data libraries, such as ENDF, JEFF, JENDL, TENDL, etc. JANIS is able to read different covariance formats: ENDF, COVERX, ERRORR and BOXER. -The nuclear data evaluation cycle (NDEC)  [13]  is used to process the JEFF-3.
3T4 and ENDF/B-VIII. 0b5 files. At the end of the processing NDEC produces two files, one HENDF and one BOXER. These files are then uploaded into JANIS database using the "Import Wizard" tool to create a new database. JANIS can also import directly covariance evaluations, such as SCALE-6. In order to more easily facilitate the input of covariances to NDaST, an automated link has been introduced to the JANIS nuclear data viewing software. From a search dialogue within the "Covariances" panel of NDaST, the user may search their public/private JANIS covariance databases for a given nuclide and reaction combination. Selection of covariance format BOXER, ENDF or COVERX returned from this search allows users to quickly calculate the propagated nuclear data uncertainty.
Checking and processing The latest beta release JEFF-3. 3 neutron library, JEFF-3. 3T4, contains 562 files, of which 447 files including covariances. The complete set of covariances is described as follows, MF31: 50 files, MF32/MF33: 446 files, MF34: 359 files, MF35: 35 files and MF40: 286 files. For the three major actinides, 235 U, 238 U and 239 Pu, their covariances are evaluated using microscopic data and nuclear models. There are three nuclear data exceptions with reduced uncertainties based on the adjustment to criticality benchmarks in the fast energy region, 235 U(nubar) and 239 Pu(n,fission) and (nubar). For the 233 U, neither PFNS covariances nor total nubar (only prompt and delayed) are given in the library. Firstly, the pre-checking of ENDF6 format has shown some inconsistencies between MF2 and MF32 in 40 files.
The processing is performed with NJOY2012. 99. Only 2 files with problems were found: 39 Ar which one of the l-state in MF32 mismatch the value given in MF2; and 9 Be a cause of the problem in NJOY2012. 99 to process MT values in the 875-890 range. Both problems were solved during this work  [14]. NJOY2012. 99 is used to generate four different BOXER files for MF31, MF32/33, MF34 and MF35. These files can be merged into a unique BOXER file to be added into the JANIS database. The 238 energy-group is selected as the energy structure to generate covariances, because this energy structure is the most common energy structure of the k eff sensitivity profiles in DICE. As an example of the use of NJOY2012. 99 to process covariance of PFNS, Figure  4  shows the input to produce covariance A special NJOY input is needed to process cross-section covariance in JEFF-3.
1 (∼290 and ∼540 pcm) and JENDL-4. 0u1 (∼125 and ∼170 pcm). Besides 239 Pu in FAST/Pu cases, other nuclides contribute to increase the k eff uncertainty. As an example, the JEFF-3. 3T4 top contributors in PMF9-1 benchmark are 27 Al(703 pcm), 239 Pu(532 pcm) and 240 Pu(182 pcm). For PMF8-1 benchmark are 239 Pu(609 pcm), 232 Th (296 pcm) and 240 Pu(180 pcm). For the Mosteller suite, we have identified the most important contributor by isotope/element and by benchmark case for the JEFF-3. 3T4 nuclear data evaluation. The following is a list of these results by element: 16.
Conclusion JEFF-3. 3T4 contains 447 files with covariance of average number of neutrons per fission (MF31), resonance parameters (MF32), cross-sections (MF33), angular distributions of elastic scattering (MF34), prompt fission spectrum (MF35) and radionuclide production (MF40). These covariances have been checked (e. g. ENDF6 format) and processed with NJOY2012. 99. The verification of these covariances have been performed with mathematical (e. g. identifying negative eigenvalues) and physical (e. g. comparison with other evaluations) procedures, as well as quantifying the impact of these covariances in criticality uncertainty analysis. Future developments in DICE/NDaST will permit to use covariance data for angular distributions. Other important feature is to extend the analysis to shielding benchmarks which will permit to quantify the impact of these covariances in other applications.
Impact of different 238 U nuclear data covariances in ICSBEP suite averaged for fissile material and spectrum. Each of the following figures shows the RSD in % of a certain reaction cross-section. JEFF-3. 3T4andENDF/B-VIII. 0b5havebeenprocessed with the code NJOY2012. 99 in BOXER format in 238 energy groups. ENDF/B-VII. 1 and JENDL-4. 0ucovariances are taken directly from NEA database in BOXER section which nubar and PFNS data are processed with NJOY2012. 99forthiswork. The SCALE-6. 2 covariance file in 56 energy groups has been imported into a new JANIS database. Figures1-3show the most important nuclide reactions that contribute to k eff uncertainty. Five different evaluations are shown in each figure.
3)and the latest JENDL-4. (NEA/WPEC)Subgroup40 since 2013. CIELO-1 cross-section data have been adopted by the ENDF project (https://www-nds. iaea. org/CIELO/). -JEFF-3. 3T4(CIELO-2). It is the latest test JEF-3. 3neutronlibrary produced via an international collabora-tion of Data Bank participating countries under the auspices of the NEA Data Bank. The efforts of JEFF in 235 U, 238 U and 239 Pu are also part of the collaboration in CIELO project. These files are the CIELO-2 set of crosssection data[1]. both experimental and model calculations; the three major actinides are evaluated with high fidelity (http:// www. nndc. bnl. gov/endf/b7. 1/). -JENDL-4. 0 released in 2005 provides the data for 79 actinides. After 2005, JENDL-4. 0 updated files (JENDL-4. 0u) are available for nuclides whose nuclear data are.
These findings led us to suggest that the ARX dup24 mutation may be a developmental model for LKA  (Curie et al. , 2014). In the present study, we performed for the first time a study of ARX expression at the protein level both during fetal human development and in an adult brain, as well as MRI morphometric analyses (1. 5 T) on 13 ARX dup24 patients compared to 13 sex-and age-matched healthy controls using FreeSurfer software, a very powerful tool both for surface, in particular cortical thickness measurement at each point across the cortical mantle, and volumetric analyses  (Dale et al. , 1999; Fischl et al. , 1999; Fischl and Dale, 2000; Fischl et al. , 2001; Han et al. , 2006;  Table  1  Semi-quantitative analysis of ARX expression in the developing central nervous system. Segonne et al.
After having clearly explained the goals of this study, all patients and their guardians gave their written informed consent in accordance with the Ethical Committee protocols of French Public Hospitals. Data were collected at CERMEP (Centre d'Etude et de Recherche Multimodal Et Pluridisciplinaire) in Lyon. Molecular screening for ARX gene was performed in laboratories from a French network dedicated to neurogenetic testing as previously described  (Poirier et al. , 2006). Age-and sex-matched healthy controls were recruited through local advertisements. Adult healthy control participants and the parents of each child included in the study signed an informed consent before the study procedure started. Thirteen ARX patients and 13 age-and sex-matched healthy controls were included in the study and completed brain MRI.
One to three sessions in the mock scanner were necessary per patient. The actual MRI session then followed. During the morphometric data acquisition (3DT1) all participants were watching a movie. Image acquisition was performed on a 1. 5 T Siemens scanner (CERMEP, Lyon). High resolution (1 × 1 × 1 mm) structural imaging with 3D T1-weighted Fast-Spoiled Gradient Recalled (FSPGR) sequence (TR/TE/TI = 1970/3. 93/1100 ms, FOV = 256 × 256 mm) was obtained for each patient and age-matched healthy control. In addition, a T2 sequence was performed (51 axial slices, FOV = 220 mm, voxel size: 0. 9 × 0. 9 × 2. 5 mm, TR/TE = 7740 /96 ms).
MRI data analysis MRI images were clinically reviewed by two paediatric neurologists from the National Reference Centre for Rare Diseases with Intellectual Disability (Lyon, France). The vermian height was determined on the T1-weighted sagittal medial view of each individual. The normality of the vermian height distribution was checked using a Shapiro-Wilk normality test. A one-way ANOVA test was applied to compare differences between groups. MRI data were processed on a Linux workstation (MGH Martinos Center, Boston, USA), using FreeSurfer software version 5. 1 (http:// surfer. nmr. mgh. harvard. edu), to reconstruct the cortical surface. FreeSurfer uses a series of computationally intensive steps on the T1weighted structural volumes to estimate the grey/white interface  (Dale et al. , 1999; Fischl et al.
Data were then aligned according to cortical folding  (Dale et al. , 1999)  and smoothed on the surface tessellation, using an iterative nearest neighbour procedure. Smoothing was restricted to the cortical surface, thus avoiding the averaging of data across sulci or outside the grey matter  (Dale et al. , 1999). This method has the advantage of matching morphologically homologous cortical areas based on the main gyri/sulci patterns with minimal metric distortion. Group analyses were performed by resampling each subject's data to the FreeSurfer average atlas. Cortical thickness maps were smoothed using a Gaussian kernel with a full width half maximum of 10 mm. Vertex-wise analyses of cortical thickness were performed with FreeSurfer. A general linear model was used to compare cortical thickness between groups with one discrete factor with two classes: ARX patients and age-matched healthy controls.
1H-K , see Supplementary data for a more detailed description). Interestingly, although most of the neuronal stem cells composing the VZ expressed ARX in the LGE, ARX was only detected in rare cells in the VZ of the MGE (Fig. 1I-J ), suggesting that neuronal stem cells have distinct identities in the MGE and LGE. ARX was also strongly expressed in migratory streams of neurons leaving the LGE and MGE (see Supplementary data for a more detailed description of ARX expression in GE). Accordingly, several ARX-positive cells migrating from the adjacent LGE were detected at the boundary between the caudate nucleus and the LGE. Similarly, streams of ARX-expressing cells were also detected in the striatal bridges connecting caudate nucleus and putamen (Fig. 2A-C ). At 32 WG, ARXexpressing cells were also detected in the nucleus accumbens which is a component of the striatum, and also a part of the limbic system (Fig.
Brain anatomical structure changes in ARX patients As we recently described a recognizable phenotype with a specific motor impairment in ARX dup24 patients  (Curie et al. , 2014) , we decided to further characterize potential neuro-anatomical distinctive patterns associated with this mutation using high quality morphometric MRI data analyzed with FreeSurfer software. This automated procedure has already been validated using both neuropathology approaches performed on human post-mortem brain  (Rosas et al. , 2002) , and manual measurements on human brain MRI  (Salat et al. , 2004). We show here that ARX patients have a significantly decreased striatal volume especially the caudate nuclei, and to a lesser extent of the thalamic and sub-thalamic nuclei, associated to a decrease in cortical thickness of the precentral gyrus and hippocampus.
Funding sources Financial support was provided from the  French Ministry of Health  ( PHRC grant   2010-A00327-32 , VDP), the  CNRS/Hospices Civils de Lyon  (research fellow postgraduate grant for AC), the  Foundation Jérôme Lejeune  (grants for AC and GF, 2013), the "Xtraordinaire" association (grant for AC 2015), the  ARRENNE association  (grant for AC, 2012 and 2014) and IBSAM (grant for GF, 2017). The authors declare that they have no conflicts of interest.
Each visit consisted of two dithered exposures. The images are reduced with the Elixir software used for the CFHTLS and modified to account for the properties of near-InfraRed (IR) data. Two series of image stacks are subsequently produced: four-image stacks for each WIRCam pointing, and one-square-degree tiles matched to the format of the CFHTLS data release. Photometric calibration is performed on stars by fitting stellar spectra to their CFHTLS photometric data and extrapolating their Y-band magnitudes. Results. After corrections accounting for correlated noise, we measure a limiting magnitude of Y AB 22. 4 for point sources (5σ) in an aperture diameter of 0. 93, over 130 square degrees. We produce a multi-wavelength catalogue combining the CFHTLS-Wide optical data with our CFHQSIR (Canada-France High-z quasar survey in the near-InfraRed) Y-band data.
The mapping of the fields was organized so as to match the CFHTLS one-square-degree tiles, with nine WIRCam pointings per CFHTLS tile. The observations were defined so as to prevent the execution of the second-visit observations in the same sequence as for the first visits, which could have generated similar persistence patterns in the data. A total of approximately 150 hours of observations were conducted during four CFHT semesters, 2010B, 2011B, 2012A, and 2012B. The observations were carefully checked by our team in the days following the observations using the Elixir-IR pre-processing package (see next section), and observations that were executed under high background conditions and/or poor seeing conditions were not validated and were subsequently reexecuted.