dataesr/scientific-paragraphs-categorization huggingface dataset:
Tumor specimens Fifty six (56) glioma formalin-fixed paraffin-embedded specimens were retrieved from the Department of Pathology data base. Thirteen (13) specimens were low grade astrocytomas (three WHO grade I, including two pilocytic astrocytomas, one infantile ganglioglioma and ten grade II, including six astrocytomas and 4 oligodendrogliomas). Ten (10) cases of anaplastic gliomas (WHO grade III) and thirty three (33) cases of polymorphic astrocytomaglioblastoma (WHO Grade IV) were also retrieved. Twelve serial sections (3 mm) were cut from each tissue-block. One was stained with hematoxylin and eosin and sequential slides were used for the immunohistochemical detection of APRIL BAFF, TWEAK, BCMA, TACI, BAFF-R and Fn14, plus a negative control. The slides were reviewed by two investigators independently and blindly (VP, ENS) and the final conclusion was reached in consensus.
Discussion The spectrum of cytokines involvement in CNS homeostasis or disease remains unclear. Among them, TNFa is locally synthesized in the CNS with several important functions, including injurymediated microglial and astrocyte activation, regulation of bloodbrain barrier permeability, stimulation of the recruitment of neutrophils and monocytes, febrile responses, glutamate transmission and synaptic plasticity  [67, 68] , while anti-TNFa antibodies have been used in brain pathologies, with impressive results  [68, 69]. Other TNF superfamily (TNFSF) members have been tried as therapeutic agents in gliomas  [40, [70] [71] [72] , with TRAIL being the best-studied  [73] [74] [75] [76] [77] [78]. In the present study we have assayed for the first time by immunohistochemistry 56 gliomas of various grade for the expression of a subset of TNFSF members, namely APRIL, BAFF and TWEAK, as well as their cognate receptors (BCMA, TACI, BAFF-R and Fn14), in parallel with a systematic search and metaanalysis of available public gene-array data for possible over-or under-expression of these molecules in gliomas, as compared to normal brain.
This method aims for the best compromise between individual chronological information for each ice core using glaciological modelling and gas and ice absolute or relative markers. This consistent timescale only covers the last 50 ka (where age markers were compiled and implemented) and does not include all deep ice cores. In this paper, together with the companion paper of  Veres et al. (2013) , we aim at producing a coherent ice and gas timescale over the last 800 ka including 5 ice cores (Vostok, EDC, EDML, TALDICE, NGRIP) without any assumption on the synchronism between climatic records and insolation or speleothem-derived tie points. We use the same strategy as the one of Lemieux-Dudon et al. (  2010 ) with some technical and methodological (SOM) improvements. In order to include the TALDICE ice core and extend the timescale prior to 50 ka, we gather a database of age markers and expand δ 18 O atm records of TALDICE and EDC.
, 2007). Middle: complete record of δ 18 O atm , blue triangles from  Dreyfus et al. (2007 Dreyfus et al. ( , 2008) )  and red triangles from this study. Bottom: precession parameter (here on a reverse y axis) obtained with the Analyseries software  (Paillard et al. , 1996) , calculated using the  Laskar et al. (2004)  solution. Black points indicate the position of tie points between δ 18 O atm and precession parameter signals from  Dreyfus et al. (2007) ; the red ones are from this study (Table  1 ). be used as orbital constraints in the gas phase for the EDC ice core (Table  1 ). Note that the δ 18 O atm ages are in agreement with the absolute dating of the Brunhes-Matuyama reversal, suggesting that we did not miss any precession cycle  (Dreyfus et al. , 2008). Buiron et al. (2011)  have measured the δ 18 O atm of TALDICE between 583 and 1402 m (9.
Orbital points database In this section, we combine the new orbital tie points derived in the previous section and the orbital tie points already available from previous studies. ice cores on the δ 18 O atm chronology  (Bender, 2002)  and TALDICE 1a age scale  (Buiron et al. , 2011; Schüpbach et al. , 2011) , respectively. Top: water stable isotope records (δD and δ 18 O ice , respectively)  (Petit et al. , 1999; Stenni et al. , 2011).
δ 18 O atm In addition to the EDC δ 18 O atm markers discussed above, we also use the markers deduced by  Suwa and Bender (2008)  for Vostok (Table  2 therein ). The tuning is slightly different than the one chosen by  Dreyfus et al. (2007)  (tuning on the 65 • N June insolation curve with a delay of 5. 9 ka instead of tuning on the precession signal with a 5 ka delay). A comparison of both tuning strategies has shown that they are equivalent  (Dreyfus et al. , 2007). Altogether, we now have a database of δ 18 O atm with 39 gas age markers for EDC and 35 for Vostok. The uncertainty associated with all these points is estimated to be a quarter of a precession period  (Dreyfus et al. , 2007) , leading to a value of 6 ka. This relatively large uncertainty accounts for the uncertainty in the choice of the orbital target and for the fact that the shift between δ 18 O atm and precession is known to vary with time, especially over terminations  (Jouzel et al.
thanks to  Sébastien Nomade  and  Frédéric Prié  for their help in this study. This project was funded by the  "Fondation de France Ars Cuttoli", the "ANR Citronnier", INRIA  and LEFE funding. The research leading to these results has received funding from the  European Union 's  Seventh Framework programme  ( FP7/2007-2013)  under grant agreement no  243908 , " Past4Future. Climate change -Learning  from the past climate". This work is a contribution to the European Project  for Ice Coring in Antarctica (EPICA ), a joint  European Science Foundation/European Commission scientific programme , funded by the  EU  and by national contributions from  Belgium, Denmark, France ,  Germany, Italy , the  Netherlands, Norway, Sweden, Switzerland  and the  United Kingdom. The main logistic support was provided by  IPEV  and  PNRA (at Dome C)  and  AWI  (at  Dronning Maud Land ).
Subjects and human brain tissues Nineteen subjects including 10 VPSPr, 6 fCJD V180I , 2 sCJD, and one fCJD T183A cases were examined. All were referred to the National Prion Disease Pathology Surveillance Center (NPDPSC, Cleveland, OH) except for an fCJD V180I case from France  [4] , and two fCJD V180I cases from Japan. The six cases with fCJD V180I were three Caucasian and three Asian patients. Written consent to use autopsy material for research purposes had been obtained from patients or legal guardians for all samples. Clinical data and relevant hospital records were coded and handled according to the protocols approved by the Ethical Committee and Institutional Review Board of Case Western Reserve University to protect patients' identities. Frozen brain tissues were processed as previously described  [7].
Immunofluorescence and confocal microscopy Immunofluorescence staining of PrP in transfected cells expressing PrP Wt , PrP V180I , or PrP T183A was performed as previously described  [11]. In brief, the cells were fixed in 4% paraformaldehyde. After blocking with PBST (10% Goat Serum, 2% T-20, 1% Triton X-100), the cells were then incubated with 3F4 (1:10,000) or calnexin (1:1,000) at room temperature, rinsed with PBS, followed with FITC-conjugated goat anti-mouse IgG at 1:1,000 (Sigma, St. Louis, MO) or Alexa Fluor 568-conjugated goat anti-rabbit as secondary antibody. Microscopy was performed using a high-speed Leica SP5 Broadband confocal microscope (Wetzlar, Germany) and HCX PL APO CS 636 oil immersion objective (NA 1. 4). Images were acquired and analyzed using Leica Application Suite software.
Acknowledgments The authors want to thank  Janis Blevins  and  Jeffrey Negrey  for coordinating brain tissues and clinical information,  Jacques Grassi  and  Stephanie Simon  for providing the Bar209 antibody,  Dr. Martin Hermann Grouschup  for providing brains of Tg mice expressing PrP glycosylation mutants,  Drs. Geoff Kneale  and  John McGeehan  for providing g5p, as well as  Dr. Janet Byron Anderson  and  Paul Curtiss  for proofreading the manuscript. Y. A. Z. was supported by a grant from the  Chinese National Key Clinical Department Project.
Experimental data During the experiment, two new and significantly extended databases have been formed through capturing screen shot images from Google earth. One database contains 100 small images with the size 128×128 obtained from the Beijing Capital International Airport; the other database consists of 10 big images with the size 5000 × 5000 obtained from Atlanta and other airports in the world. To obtain clearer images of the aircrafts, eye altitude is set to lower than 500 m when using Google Earth to obtain screenshots. Aircraft targets from the airport are selected as experimental targets from which the training and testing image samples are taken. At least one image is needed for training. We use ten images for training in the experiments.
Thus, EMContourMRF obtains better contours of objects; (3) EMContourMRF combines EM iteration and GraphCut optimization to estimate and to optimize the distribution models of objects and backgrounds repeatedly. EMCon-tourMRF has relatively higher segmentation precision than object detection methods that are based on shape fragments. The accuracy of object detection and segmentation is significantly affected by shadows. Thus, the removal of shadows is the focus of our follow-up work. Moreover, with the development of network information, automatic acquisition of images that contain more objects to construct a complete training database is a key step in our follow-up work to achieve better segmentation results independently.
Our conclusions are summarized in §11. The cosmological parameters used throughout the paper are: H0=70 km/s/Mpc, ΩΛ=0. 7 and Ωm=0. 3. Magnitudes are reported in the AB system and we will use the Salpeter initial mass function (IMF) unless otherwise stated. Table  1. Summary of the datasets used in our analysis. The "Type" column refers to spectroscopy (S) or imaging (I).
HERSCHEL OBSERVATIONS AND DATA REDUCTION The Herschel observations of XMM2235 were carried out as part of two programs, one in guaranteed time (GT1, PI Altieri) and one in open time 1 (OT1, PI Popesso). The PACS 100/160µm imaging data were taken within the scope of the 100h OT1 program designed to study the FIR star formation history of a sample of 8 X-ray selected galaxy clusters at 1. 4 < z < 1. 8, and investigate the relation between star formation activity and environment at the epoch when clusters are assembling galaxies at a faster rate than today and galaxies are still undergoing their own formation process. The results obtained for the complete cluster sample observed in this program will be presented in forthcoming papers. The SPIRE 250/350/500µm imaging data were taken in the context of the smaller and shallower GT1 program, aimed at studying the evolution of star-formation in 8 highredshift clusters within the range 0.
PACS observations and catalog The PACS  (Poglitsch et al. 2011 ) observations were acquired in December 2011  (ObsId = 1342234105, 1342234106, 1342234430, 1342234431) , amounting to a total of ∼24 h. The full data reduction of the data considered here in addition to the full dataset of the original PACS Program are described in  Popesso et al. (2012 in prep. ). Here we summarize the main steps. Data are processed through the standard PACS data reduction pipeline in the Hipe environment  (Ott et al. 2006) , with the addition of some custom procedures, aimed at removal of instrument artifacts. These procedures comprise: iterative masking of the sources for avoiding residuals due to the high-pass filtering implemented in the PACS pipeline. Visual inspection of scan legs to flag and discard scan legs affected by interferences in the blue channel.
Offsets and errors in the pointing of the Herschel satellite are corrected by re-centering the data on a grid of known bright priors. The map coaddition and error estimation is performed through a weighted mean of several maps with the same WCS. The PACS catalogs at 100 and 160 µm are created via a blind extraction using the Starfinder PSF-fitting code  (Diolaiti et al. 2000). Flux reliability, incompleteness and spurious source fraction are estimated and tested via Monte Carlo simulations. Dedicated IDL proce- dures, described in  Popesso et al. (2012)  are used to check the effect of the high-pass filtering task on the source flux in different flux bins by adding fake sources on the PACS pixel timeline. See also  Berta et al. (2011 ), Lutz et al. (2011)  for further details about source extraction and data reduction.
ANCILLARY MULTI-WAVELENGTH DATA The galaxy cluster XMM2235 benefits from an extensive multi-wavelength coverage, including deep, high-resolution X-ray data from Chandra, optical imaging with the Hubble Space Telescope, near-infrared (NIR) imaging with VLT/HAWK-I and spectroscopic data with VLT/FORS2 taken over a large field-of-view. Details on the optical and NIR data used here can be found in  Strazzullo et al. (2010)  and  Lidman et al. (2008)  respectively. The high-quality, high-resolution Ks-band data obtained over a large FOV (13. 5 ×13. 5 ) nearly matches the area covered with PACS. This broad dataset is fundamental to the analysis of the Herschel data which suffer from blending, and confusion only in the longest wavelengths. For our analysis we use an extensive spectroscopic campaign based on 4 VLT/FORS2 masks using both the MOS and MXU modes, described in  Rosati et al.
Using our extensive spectroscopic and photo-z catalogs we find that twenty-five narrow-band emitters are cluster members (of which 10 have spectroscopic redshift), and 14 are interlopers (of which 7 have spectroscopic redshift). For the remaining 20 narrow-band emitters we do not have redshift information. We would expect a higher correspondence between the Hα galaxy candidates and our FIR data, relative to the spectroscopically confirmed members, since the former are mostly star-forming by definition. There is, nonetheless, the possibility that extinction plays a prominent role, preventing highly star-forming galaxies to be seen in the narrow-band observations. We use the Spitzer /IRAC data taken in 2005 (PI C. R. Mullis, prog ID 20760), which is important to ensure a proper identification of the sources seen in Herschel and link them to the optical/near-IR.
The four-channel data were retrieved from the archive and reduced with standard procedures. Source extraction was performed in Point Response Function (PRF) multiframe mode within APEX. The PRFs used in the process were the default ones provided by the Spitzer Science Centre. The data processing was performed with the tool mopex 18. 5 using the standard parameters included in the mopex pipeline provided by the Spitzer helpdesk. We perform blind source extraction for each band and PSF-fitting photometry using mopex. Sources below the 5-σ detection thresholds ([0. 0044, 0. 0045, 0. 0060, 0. 0062] mJy at  [3. 6, 4. 5, 5. 8, 8]  µm, respectively) were discarded. XMM2235 was observed with the Chandra ACIS-S detector in VFAINT mode with a total effective exposure time of 196 ks (PI Mullis). The full data analysis and reduction were published in  Rosati et al.
FIR SED FITTING OF INDIVIDUAL DETECTIONS In this section we perform a standard SED-fitting of the infrared range with the widely used SED fitting code LePhare   2003 ) templates (BC03) for the near-infrared part of the spectra. To ensure a proper identification of the cluster members in the Herschel maps we first performed a visual identification of all member galaxies in the Ks, IRAC and PACS images (see Fig. 2 , 3). We then matched the PACS catalog with the spectro-photometric catalogs using a nearest match algorithm with a search radius of 5. Blending affects some of the detections making a precise decontamination too difficult. In such cases, we take the following considerations to evaluate whether the FIR emission originates from the cluster member: (i) check whether the cluster member has  [OII]  or Hα emission as an indication of SF, (ii) investigate the properties of the contaminants using our spectrophotometric catalogs, (iii) evaluate the spatial separation between the target galaxy and contaminant and how the relative emission of the galaxies evolves from the K-band, 8µm, 100µm to the 160µm images (see Fig.
STACKING ANALYSIS In addition to the study of the cluster galaxies individually detected by PACS, we also constrained the star-formation of the cluster members that are potentially star-forming but do not have a detection in the FIR, as has been done in e. g. ,  Dole et al. (2006). We performed a mean stacking analysis using the IDL stacking software of  Bethermin et al. (2010)  and  Bavouzet (2008)  on the residual maps at 100µm and 160µm of two samples without PACS detection : (1) the spectroscopically confirmed members with indications of on-going star-formation, and (2) the narrow-band emitters with a spectroscopic or photometric redshift within 2-σ from the cluster redshift. We tested the stacking procedure with simulations of dozens of gaussian sources with fluxes below the 3-σ limit randomly placed in the residual maps and we recovered, within a very good agreement, the input fluxes, therefore we find the method to be robust.
Of these, eleven PACS candidates are found to be spectroscopic interlopers, three more are photo-z interlopers, and after a visual screening of the individual galaxies in the PACS and the Ks-band data we discard 5 additional sources which are considered spurious or for which we have a low S/N. Of the remaining 41 sources listed in Table  4 , one is the spectroscopic member ID 5, and six have a photometric redshift within a range of 0. 15 from the cluster redshift. We note that not all cluster members listed in Table 2 are included in this sample, since for most of those cluster galaxies we do not have 3-σ fluxes in both PACS bands. Nonetheless, we confirm that generally their SEDs satisfy our flux selection criterion, with the exception of ID 2669, which has F160=4. 9±1. 24 mJy and F100= 5.
CONCLUSIONS In this paper we have characterized the far-infrared properties of the galaxies (confirmed and photo-z candidates) in XMM2235, a massive cluster at z=1. 4, using deep Herschel imaging data from 100-500 µm. The extensive ancillary data of this cluster is crucial to ensure a proper identification of the cluster galaxies in the Herschel maps, and to further characterize the properties of the highly star-forming members. We summarize our main results here: (i) we derived star-formation rates for the 13 spectroscopic and photo-z members in the range 89-463 M /yr, all of them lie outside the core at r > 250 kpc from the center and extend well beyond R500; (ii) we obtained a significant stacking signal of 9 spec-troscopic members that were not individually detected by PACS, corresponding to a SFR = 48±16 M /yr; (iii) we find that 4 of the 6 spectroscopic members detected by PACS are associated with AGN X-ray emission, although the data did not allow for a decomposition of the FIR emission into an AGN and host components; (iv) we performed a visual morphological classification of a subsample of nine members with HST/ACS data which show that these high star-forming galaxies are all late-types; (v) we find that SFR (Hα) is a factor 5-10 lower than SFR (IR), which indicates that a dust extinction of about 3 magnitudes in Hα; (vi) the sSFR-M * relation shows that all cluster members with FIR emission are starburst galaxies that follow the same trend as field galaxies at the same redshift; (vii) we selected a sample of 41 FIR cluster member candidates using a color criterion based on the shape of the SED.
Six of the thirteen individual detections are beyond a radius of 1 Mpc, approximately the cluster virial radius, therefore most of the measured FIR star-formation in this cluster occurs in potentially infalling galaxies at the edge of the cluster X-ray emission. We note, however, that current studies providing evidence for an increase of SF in the centers of distant clusters used MIPS 24µm data and thus had a lower limit to the star-formation rate. The study presented here on the individual system XMM2235 is part of a larger project including more than a dozen galaxy clusters reaching the proto-cluster regime, that will allow us to characterize star-formation activity at different cosmic times and stages of evolution.
ACKNOWLEDGMENTS JSS thanks  D. Elbaz  and  R. Gobat  for useful discussions and  R. Grützbauch  for sending us the yet unpublished catalog of revised SFR of the Hα emitters. R. D. acknowledges the support provided by the  BASAL Center for Astrophysics and Associated Technologies  and by  FONDECYT  N. 1100540. C. L. is the recipient of an  Australian Research Council   Future Fellowship  (program number  FT0992259 ). PACS has been developed by a consortium of institutes led by  MPE (Germany)  and including  UVIE (Austria) ;  KUL, CSL, IMEC (Belgium) ;  CEA, OAMP (France) ;  MPIA (Germany) ;  IFSI, OAP/AOT ,  OAA/CAISMI, LENS, SISSA (Italy) ;  IAC (Spain). This development has been supported by the funding agencies  BMVIT (Austria) ,  ESA-PRODEX (Belgium) ,  CEA/CNES (France) ,  DLR (Germany) ,  ASI (Italy) , and  CICYT/MCYT (Spain).
It is therefore sufficient to prescribe the cardiac output to ensure the comparability of different solutions. A value of 5 L /min was imposed, which represents a physiologically plausible value for an adult person at rest  [26]. In the model used, this value implied a mean systemic arterial pressure of 100 mmHg. The results presented could also be reproduced for other perfusion levels. The fixation of the total cardiac output to 5 L /min is also justified by the fact that the current study did not investigate the effect of the VAD actuation on the perfusion, but was focused on the heart-VAD interaction. The model of the cardiovascular system used here was originally published in  [24]. An implementation in MATLAB/SIMULINK R (The Mathworks Inc. , Natick, MA, USA) of this model was used earlier  [25].
In order to always obtain the least possible number of evaluations of the objective and the model functions, the Jacobian matrix was constructed by custom code and was then passed to the NLP solver. Linear terms Equations (9d)-(9f) have constant derivatives, whereas simple bounds Equations (9g)-(9h) are handled directly by the NLP solver. The derivatives of objective function Equation (9a) and of defect constraints Equation (9b) were constructed from the derivatives of the objective and the model functions, which were calculated analytically. As an NLP solver, SNOPT was used  [39]. Iteratively refining the problem discretization and providing the Jacobian matrix to the solver reduced the typical runtime for solving one OCP from about 30 min to less than 1 min. This reduction in computational time enabled large-scale parametric studies and a quick comparison of various problem formulations.
An optimized speed trajectory was realized using a modified speed controller for the blood pump. After several cardiac cycles, stationary operation was reached, as imposed within the OCP by periodicity conditions Equations (6e) and (6f). Upon reaching steady state, the data from the last cardiac cycle was stored for further analysis. The pressures in the two reservoirs, representing the up-and down-stream pressures of the blood pump, as well as the pump speed and flow rate were measured. In addition, all relevant data from the numerical simulation were saved along the measured signals.