dataesr/scientific-paragraphs-categorization huggingface dataset:
A2 The SPIRALE in situ infrared spectrometer A detailed description of the instrumental characteristics of SPIRALE and of its operating mode can be found in  Moreau et al. (2005). Six tunable laser diodes emitting in spectral micro-windows (< 1 cm -1 ) in the mid-infrared domain (1250 to 3000 cm -1 ) are used for in situ measurements of trace gas species from the upper troposphere to the stratosphere. The six laser beams are injected into a multipass Heriott cell, comprising two mirrors spaced 3. 50 m apart by a telescopic mast, allowing for 434. 0 m optical path. This cell is deployed under the gondola during the flight above ∼ 9 km altitude, i. e. when pressure is below ∼ 300 hPa and thus absorption lines are significantly narrower than the scanned micro-windows. Species concentrations are retrieved from direct absorption, by fitting experimental spectra with spectra calculated using the HITRAN (high-resolution transmission molecular absorption database) 2012 database  (Rothman et al.
A4 The SALOMON remote-sensing UV-visible spectrometer The data presented in this study were obtained using a Système d'Analyse par Observation Zénithale (SAOZ)-type UV-visible spectrometer  (Pommereau and Piquard, 1994)  connected to a sun and moon tracker for the detection of ozone and NO 2 amounts. The one-band spectral window of SALOMON between 400 and 950 nm is adequate for the retrieval of absorption features over large spectral ranges, i. e. roughly from 400 to 680 nm for ozone and from 400 to 550 nm for NO 2. The spectrum recorded at float altitude (more than 36. 5 km) corresponds to a minimum air mass and is considered as a reference spectrum. Occultation spectra recorded for elevation angles between 0 and -5 • below the gondola horizon are taken into account for the retrieval of the SCDs.
Owing to the thermal insulation of the spectrometer, no spectral drift of the Fraunhofer lines and no instrumental resolution changes have been observed between the reference and the occultation spectra. The Rayleigh scattering contribution is calculated and removed from the spectra using these profiles and the spectral cross sections given by  Bucholtz (1995). Then, O 3 and NO 2 SCDs are determined by least-squares fits using the University of Bremen high-resolution absorption cross sections convolved to the spectral resolution of the instrument (data available from http://www. iup. uni-bremen. de/gruppen/ molspec/databases/index. html). Aerosols are a major lowfrequency spectral contribution, which is removed by a highpass filter to derive the NO 2 SCDs. All lines of sight are not used to derive SCDs since the retrieval is performed only when signal-to-noise ratios (computed in our case by the ratio of the fit maximum amplitude to the standard deviation between the measurement and the fit) are greater than 1.
NO 2 fitting errors are typically 5-9 % for SCDs crossing the altitude levels of the volcanic aerosol layer (i. e. below ∼ 19 km). Vertical concentration profiles have been derived using an a posteriori least-squares inversion technique  (Rodgers et al. , 2000) , taking into account the fitting error and the uncertainties of the cross sections. Note that the data reduction method used in this study is described by  Renard et al. (2000)  and  Berthet et al. (2002). For the flight presented in this study we have added an HR4000 UV spectrometer from Ocean Optics to detect BrO absorption lines in the 346-360 nm range as done for the DOAS instrument. The spectrometer is thermally insulated and regulated using Peltier devices to avoid spectral shifts. It has its own connection to the sun tracker but collects the sunlight simultaneously with a Jobin Yvon UV-visible spectrometer.
Acknowledgements. The authors are grateful to the  CNES  ( Centre National d'Etudes Spatiales ) balloon launching team for successful operations and the  Swedish Space Corporation at Esrange. The  StraPolÉté  project and the associated balloon campaign has been funded by the  French "Agence Nationale de la Recherche " ( ANR-BLAN08-1-31627 ),  CNES , and the " Institut Polaire Paul-Emile Victor " (IPEV). The study is supported by the  French Labex "Étude des géofluides et des VOLatils-Terre ,  Atmosphère et Interfaces -Ressources et Environnement" (VOLTAIRE)  ( ANR-10-LABX-100-01 ) managed by the  University of Orleans. The ETHER database ( CNES-INSU/CNRS ) is a partner of the project. Further support for the DOAS balloon measurements came through the  Deutsche Forschungsgemeinschaft, DFG  (grants  PF-384/5-1  and  384/5-1  and  PF384/9-1/2 ) and the  European projects EU projects Reconcile  ( FP7-ENV-2008-1-226365 ) and SHIVA ( FP7-ENV-2007-1-226224 ).
RT-qPCR, in situ hybridization, microarray, and sequencing RT-qPCR was performed using gene-specific primers and probes (Supplemental Table  1 ). In situ hybridization, microarray and RNA-seq were performed as described  (21). ChIP-seq was performed as described using tumor from mice  (22). Experimental details and data analyses are described in Supplemental materials and methods. Array and sequencing data are available from NCBI (SuperSeries GSE98302 with the SubSeries GSE98298, GSE98299, GSE98300, and BioProject PRJNA384622).
Acknowledgments We thank members of the laboratory for helpful discussions. We are grateful to  Dr. Kathleen Millen  ( Seattle Children's Hospital Research Institute, USA ) and  Dr. Ryoichiro Kageyama  ( Institute for Virus Research Kyoto University, Japan ) for providing Lmx1a-Cre mouse strain and pCI-RAGE-Math1-IRES-LacZ vector, respectively. We are indebted to  Claire Evans ,  Jessica Zylla ,  Sara Maria Cigna ,  Sophie Leboucher ,  Coralie Lefevre ,  Christophe Roulin ,  Hamasseh Shirvani , and  Hua Yu  for excellent technical assistance.
Financial support:  L. Bihannic  was supported by a PhD fellowship from the Ministère français de l'enseignement supérieur et de la recherche and Ligue nationale contre le cancer. O. Ayrault is supported by  Marie Curie Integration  grant  FP7-PEOPLE-2011-CIG 294010 ,  CNRS ,  Inserm , and  Institut Curie. M. D. Taylor  is supported by The  Canadian Cancer Society Research Institute. E. Zeng  is supported by the  University of South Dakota Faculty Startup Fund. E. Zeng  and  A. H. Heglin  are supported by an  Institutional Development Award (IDeA)  from the  National Institutes of Health (NIH)  under grant number  P20GM103443  and  South Dakota BioSystems Networks & Translational Research  through the  National Science Foundation/EPSCoR  Award # IIA-1335423. H. Zhao is supported by  Sanford Research, Matthew Larson Foundation , and IDeA from the  NIH  under grant number  5P20GM103548  (Cancer), and  1P20GM103620-01A1  (Pediatrics).
The availability of qualified computational tools and nuclear data are pre-requisites for performing the analyses as required for the nuclear design, optimization and performance evaluation of the key facilities, ITER, ENS and DEMO including the assessment of safety, licensing, waste management and decommissioning related issues. The needs for high quality nuclear data are addressed by a Consortium on Nuclear Data Development and Analysis which provides the relevant services on the production of nuclear data evaluations and data files including a e-mail: ulrich. fischer@kit. edu their validation for neutronics design and activation calculations. In the following, an overview is presented on the related Nuclear Data Development (NDD) activities of the Consortium with focus on the recent achievements in the areas of nuclear data evaluations, benchmarking and validation, nuclear model improvements, and uncertainty assessments.
European NDD programme for fusion The development of nuclear data for fusion technology in Europe is organized by Fusion for Energy (F4E), the European Joint Undertaking for ITER and the Development of Fusion Energy, Barcelona, Spain. A dedicated NDD programme is conducted which aims at providing a well-qualified nuclear database and validated computational tools for neutronics and activation calculations as required for the design, licensing and operation of the key facilities ITER, ENS and DEMO. The programme is executed by a Consortium on Nuclear Data Development and Analysis which combines available European expertise on nuclear data evaluation, processing, validation and benchmarking. The Consortium consists of the research institutions KIT (Karlsruhe, Germany), CCFE (Culham, UK), NRG (Petten, The Netherlands), JSI (Ljubljana, Slovenia), TUW (Vienna, Austria), CIEMAT with UPM and UNED (Madrid, Spain) and IFIN-HH (Bucharest, Romania).
The Consortium provides the requested services on nuclear data evaluations relevant to the various fusion applications including nuclear data for neutron, proton and deuteron induced reactions, the generation of associated co-variance data for uncertainty assessments, the development of advanced nuclear models and codes, the processing and benchmarking of the evaluated data against integral experiments, as well as the development of suitable software tools for sensitivity and uncertainty analyses of fusion systems. According to the actual priorities of the ITER project, ENS and DEMO needs, dedicated NDD work programmes are specified in close agreement of F4E and the Consortium. The requested activities are then conducted by the Consortium through specific grants awarded by F4E. These activities are complemented with a parallel scheme on nuclear data experiments and measuring techniques conducted by another consortium.
KIT employs the Universal Monte Carlo (UMC) approach  [9]  to generate covariance data taking into account both nuclear model and experimental uncertainties as implemented in KIT's BEKED code system  [10]. TUW utilizes the Full Bayesian Evaluation Technique (FBET)  [11]  implemented in the GENEUS system  [12]  to provide evaluated crosssections with associated uncertainty information. Model parameter uncertainties are accounted for as well as model deficiencies. The focus of TUW's recent work was actually on the development of a consistent evaluation procedure for neutron-induced reaction data of light nuclei. An adapted R-matrix approach was developed, based on a coupledchannel model with background potentials  [13]. This allows a continuous matching of the reaction data with statistical model calculations as provided e.
g. by TALYS. Thus a smooth transition from the R-matrix regime to the statistical model regime can be achieved. A generalized Rmatrix code has been developed and integrated as module in the general reaction code system GECCCOS  [14]. Several verification tests were performed showing perfect agreement with results of the FRESCO code  [15]  for elastic and inelastic reactions. The ability to describe the resonance region with a smooth transition to pure potential models was demonstrated for the total, elastic and (n,α) cross-section of 16 O in the energy range 1-6. 2 MeV. As an example, Fig. 1  shows the total cross-section in the energy range 1 to 3 MeV as predicted by the adapted R-matrix representation with a background potential. A prototype ENDF data file was produced for 16 O comprising the R-matrix generated data in the energy range 1 to 3 MeV, data associated with the background potential between 3-6 MeV, and TALYS evaluated data above 6 MeV up to 200 MeV.
Benchmark analyses for specific shielding and tritium breeding calculations With these activities the status of the available nuclear data evaluations was assessed with regard to their use in shielding and tritium breeding calculations. Relevant iron shielding benchmarks from the recently updated SINBAD compilation [18] were utilized to check the Fe data evaluations. These included the "ASPIS IRON-88", "JANUS phase I", "ASPIS NESDIP 3", and the "EURACOS Fe" experiments. The analyses revealed a general good performance of the new iron data evaluations (Sect. 3. 1). As an example, Fig. 3  shows the C/E (calculation/experiment) ratios obtained for the 103 Rh(n,n ) reaction rate measurements in the "ASPIS IRON-88" experiment. (The red curve labelled "MCNP CIELO" stands for the recent Fe nuclide evaluations provided in the frame of the NDD programme for fusion technology, see Sect.
Sensitivity/uncertainty tools and application analyses The issue of sensitivity/uncertainty (S/U) assessments, including related tool developments and application analyses, is also addressed within the NDD activities. The aim is to enable the identification of important reactions for relevant responses such as the tritium production, and quantify associated uncertainties on the basis of available co-variance data. In the framework of previous NDD activities, related development work has been conducted on the deterministic S/U code SUSD3D  [21]  by JSI, and on the MCNP based Monte Carlo sensitivity code MCSEN  [22]  by KIT with the Hebrew University of Jerusalem, including the adaptation of MCSEN to MCNP5. Within the recent NDD activities, the coupling of SUSD3D with the 3D discrete ordinates / finite elements code ATTILA  [23]  was investigated.
ATTILA offers advanced features such as the use of unstructured 3-D tetrahedral meshes and the possibility to import CAD geometry data through the translation to a mesh grid. On the basis of a simple one-group test case it was shown that coupling of ATTILA and SUSD3D is feasible although additional development effort is required to provide a fully tested general coupling scheme. With the MCSEN code it is possible to use for the sensitivity calculations the same MCNP model as applied in design calculations. On this basis, uncertainty estimates can be obtained for a real fusion reactor configuration without approximation in the geometry representation. This capability was tested for a DEMO model developed within the PPPT programme  [24]. The sensitivity and uncertainty of the TBR were calculated for the reactions on the major nuclides including 1 H, 6 Li, 7 Li, 9 Be, 16 O, 28,29,30 Si, 54, 56 Fe, 52 Cr, 58 Ni, and 182,183,184,186 W.
The related covariance data were taken from JEFF-3. 2 whenever available, from FENDL-2. 1 for 7 Li, from EFF-3 for 9 Be and from JENDL-3. 2 for 16 O. For comparison purposes, covariance data from the TENDL-2014 library were also used. The TBR was shown to be predominantly sensitive to the 16 O data, followed by 6,7 Li, 28 Si, 9 Be and 56 Fe. An overall uncertainty of ±3. 2% was obtained for the TBR when using JEFF-3. 2 covariance data with the mentioned additions. The uncertainty is dominated by the uncertainties coming from the 16 O, 6 Li and 7 Li cross-sections. When using TENDL-2014 covariance data, the uncertainty estimate increases to ca. ±10%.
Gas production cross-section data for Z = 12 to 83 nuclides In addition to the displacement damage, the production of gases like hydrogen and helium strongly affects the behaviour of materials under irradiation. In particular this applies for the material irradiation with high energy neutrons in fusion devices and the IFMIF/ENS facility. To enable a reliable assessment of the gas production in these facilities, a systematic evaluation of gas production crosssections was performed for nuclides ranging from Z=12 to 83. This evaluation is based on available experimental data, nuclear model calculations and systematics  [29]. Figure  6  shows, as example, the helium gas production cross-section evaluated for Cr including the available experimental data. The curve labelled "after correction using 96 MeV data" applies for the prior evaluation using mass dependent cross-section data obtained for a wide range of nuclei at 96 MeV on the basis of experimental data.
Improved TENDL activation cross-sections The EAF (European Activation File) series of activation data libraries for fusion applications was terminated with EAF-2010  [30]. The strategy in the European Fusion Programme is to adopt in future TENDL as reference data library for activation calculations. Significant efforts were thus undertaken to ensure that TENDL can actually preserve or increase the quality of EAF-2010 by including the variety of validated cross-sections and improving deficient data. Validation analyses performed by CCFE on a large set of integral experiments showed that TENDL-2014 actually is outperforming EAF-2010 as data library for fusion relevant activation calculations  [31]. To further increase TENDL's quality as an activation data library, a priority list of relevant reactions was elaborated for which discrepant or deficient cross-sections were found, either with regard to differential or integral experimental data, or unphysical characteristics.
The list was prioritised with regard to the importance of reactions for fusion applications including, in particular, the activation of concrete in ITER and the IFMIF facility. The related analyses on the ITER bio-shield showed that TENDL-2014 produces consistently higher activity and dose rate values than EAF-2010. Some discrepancies were also found for the concrete irradiation in IFMIF. The final list of reactions to be improved encompassed 97 reactions. All of these cross-sections were updated on the basis of nuclear model calculations with the TALYS-1. 8 code and recent experimental data whenever available. Figure  7  shows the example of the 16 O(n,p) 16 N activation cross-section which in the high energy range above 20 MeV had to be reduced as compared to TENDL-2015 (The curve labelled "TALYS" refers to the updated cross-section).
Deuteron induced activation cross-sections High quality cross-section data of deuteron induced reactions are required to assess the generation of activation products and secondary neutrons in the accelerator facility of IFMIF/ENS. The recent evaluation effort in this field was on the deuteron cross-sections of the stable Ni isotopes 58,60-62,64 Ni to up to 60 MeV. In the evaluation, contributions of all involved reaction mechanisms were taken into account including break-up, stripping, pickup, pre-equilibrium and evaporation processes  [32]. The comparison to TENDL-2015 and experimental data (Fig. 8 ) demonstrates the improvement obtained with this approach.
MCUNED code extension for deuterons MCUNED is an extension to the MCNPX Monte Carlo code including the capability to handle deuteron data libraries in the transport simulation with the production of secondary particles  [37]. Within the recent NDD activities, MCUNED was further enhanced to represent in the deuteron transport simulation directly the deuteron break-up process based on the recent Kalbach formalism. This allows representing the angular distribution of the secondary particles emitted in the break-up reactions with analytical formula including two parameters which need to be stored on the evaluated ACE-type data files used by MCUNED. A new compliant TENDL data library has been produced for all stable isotopes. Test calculations performed with MCUNED for Al and Cu targets showed a significant improvement as compared to previous simulation results with a very good agreement to the measured emission spectra.
Conclusions and outlook The strategic approach adopted in the EU for the development of nuclear data for fusion technology was outlined and the major recent achievements were ND2016 presented. The related R&D activities have been conducted so far by the Consortium on Nuclear Data Development within a Partnership Agreement with F4E, Barcelona. The NDD activities will be transferred to EUROfusion and implemented in the PPPT programme to directly serve the nuclear data needs for neutronics analyses of DEMO and IFMIF/ENS.
According to the Beer's law, the transmissivity should be an exponential function of the optical thickness, which depends linearly on the LWP  (Stephens, 1978) , Tr5exp 2aLWP ð Þ ; (12) Fitting this function to the LES data yields a51=55: W 21 m 2. The SCMs reproduce this relation, which is encouraging, but the spread in transmissivities at a given LWP is significant. This spread is similar to that reported by  Siebesma et al. (2004)  and  Bretherton et al. (1999) , and is related in part to variations in cloud cover. However, the SCM ensemble also includes some excessive LWP values (see Figure  7 ). In this area of the diagram, the exponential fit should be interpreted with caution, because (i) it assumes full cloud   1. As explained in the text, the dashed lines represent either theoretical models or fits proposed in the previous literature.
Acknowledgments The research presented in this paper has received funding from the  European Union ,  Seventh Framework Programme  ( FP7/2007(FP7/ -2013 ) ) under grant agreement  244067. P. N. Blossey  acknowledges support from  NOAA MAPP  grant  GC10-670a  as a part of the  NOAA Sc-Cu Transition Climate Process Team. Computational support was provided to  A. Ackerman  by the  U. S. DOE National Energy Research Scientific Computing Center  and the  NASA Advanced Supercomputing Division  for the DHARMA simulations. V. Larson  and  N. Meyer  acknowledge financial support under grant  AGS-0968640  from the  U. S. National Science Foundation. S. Dal Gesso  has received funding from the '' Energy Transitions and Climate Change '' project supported by the  Excellence Initiative of the University of Cologne.
Acknowledgements. We are grateful to all  SLF  colleagues who assisted in field data collection. We thank  Benjamin Reuter  for the SMP-derived specific fracture energy data and for insightful discussions and comments on the paper. We acknowledge the constructive comments of two anonymous reviewers as well as Ned Bair who helped us to improve our paper. Johan Gaume  has been supported by the  Ambizione  grant of the  Swiss National Science Foundation  ( PZ00P2_161329 ). Edited by: E. Larour Reviewed by:  E. H. Bair  and two anonymous referees.
This is due to the relatively high variability between the respective PPI interfaces. This variability might allow for the development of compounds that specifically bind to unique composite pockets at the PPI interfaces. In this Figure  2. Representative examples of competitive, allosteric, and stabilizing PPI ligands (X-ray structure (above), chemical structure (below)). (A) p53/ hDM2 inhibitor RG7112 (PDB ID: 4IPF). 43 (B) BH3/Bcl-2 inhibitor ABT-199 (PDB ID: 4MAN). 31 (C) Fragment of BRD4/Histone inhibitor I-BET762 (PDB ID: 4C66). 32 (D) HIF-2 PAS domain allosteric modulator (PDB ID: 4GHI). 35 (E) FKBP12/Rapamycin/FRAP stabilizer complex (PDB ID: 1FAP). 40 (F) Transthyretin stabilizer (PDB ID: 2FLM). 42 ay, not only can tool compounds be developed for the study of the underlying biology in, e.
68 A survey of the recent literature has highlighted a number of reports showing the role of, and in a few cases the structural features of, 14-3-3 from parasites, which are briefly reviewed here. Plasmodium falciparum and Plasmodium knowlesi are two species of protozoan parasites that can cause severe malaria infection in humans. 69 In P. falciparum and P. knowlesi, the single isoform of 14-3-3 was shown to act as a chaperone only in specific life stages of the parasite. 68 In Plasmodium berghei, the host skeletal protein dematin is translocated from the erythrocyte membrane within the parasite, where it interacts with the Plasmodium 14-3-3, thus influencing the remodeling of the. 14-3-3 structure and binding of partner protein peptides exemplified by the 14-3-3ζ/C-Raf complex (PDB ID: 4FJ3).
44, 49, 65, 86 The fact that 14-3-3 proteins serve purely as adapter proteins means that active compounds against 14-3-3 alone will impact several binding partners and thus likely give rise to unwanted pharmacology. However, if the drugs target the complex formation between 14-3-3 and a protein partner, either by inhibition or stabilization, then intrinsic specificity should be possible. 24 tructural Biology of 14-3-3 PPIs. Most PDB entries of 14-3-3 crystal structures represent binary complexes of 14-3-3 with a peptide mimic of the phosphorylated binding site of the PPI partner protein. Only in a limited number of cases has crystallization of 14-3-3 with a larger part of the partner protein been possible. One reason for the difficulty in obtaining fulllength structures of these complexes is the fact that the partner proteins themselves are often multidomain proteins and thus challenging to crystallize.