dataesr/scientific-paragraphs-categorization huggingface dataset:
7  therein), and whose material parameters may be independently tested by both laboratory and geophysical observation, must be considered. The peak uplift predicted by our best fit Earth model is 47 mm/yr located in the Hektoria/Green glacier basin (Fig. 5c ), corresponding to the geographical location of the largest mass loss  (Berthier et al. , 2012). The peak uplift is dominated by the elastic signal and has a small spatial extent, diminishing to 30 mm/yr or less within ∼ 30 km. Our nearest cGPS site is located at Foyn Point (FONP), ∼ 40 km away, where the observed uplift rate of 14. 9± 2. 7 mm/yr agrees well with the 16. 4 mm/yr predicted by the model. Our rates may differ from the true uplift for parts of the model domain if the long-term background uplift rate is substantially different to the spatially constant term we have adopted; however, the closeness of the fit between the LARISSA cGPS data and our model predictions suggests our first approximation is reasonable.
In view of this we consider the implications of an Earth model with a more complex structure in the top 400 km. Several studies that have used a more complex Earth structure include a low viscosity zone (LVZ) directly beneath the elastic lithosphere (e. g. ,  Sato et al. , 2011). We performed some sensitivity tests to investigate whether such a model could provide a better fit to the data. Two thicknesses of the LVZ were tested (100 km and 200 km), along with several different ratios of LVZ viscosity to upper mantle viscosity (1:5, 1:10, 1:20) (six experiments in total). The results showed that whilst the single best fitting Earth model changed for each experiment, the overall range within the 95% confidence limit remained broadly the same. Furthermore, the minimum RMS misfit did not improve by more than 1%, demonstrating that a significantly better fit to the data could not be achieved with a more complex Earth model.
Sensitivity to ice model uncertainties As described in Section 2, we modelled ice-mass change over a longer time period than is covered by the elevation change data by linearly extrapolating a constant rate of ice loss backwards and forwards in time from a few months after ice shelf break up to the present day, with no ramp up of mass change included. Studies have suggested that glaciers in the NAP that have accelerated following an ice shelf collapse remain at elevated speeds for decades. Rott et al. (2008)  showed that Drygalski glacier, feeding the former Larsen A Ice Shelf, did not accelerate between 1999 and 2007, and  Rott et al. (2011)  state that the increased velocity of the Larsen A and Prince Gustav glaciers has so far been maintained 15 years after ice shelf collapse. The uncertainties in our ice model therefore relate to how quickly Larsen B glaciers accelerated to reach the 2002-2006 rates (Fig.
Elastic effects of surface mass balance anomalies Whilst the model output closely matches the cGPS time series overall, there are localized misfits. This is likely due to local time variable mass changes which are not included in our ice loading model. We investigated the possibility that these fluctuations are caused by an elastic response to variations in surface mass balance (SMB) over shorter periods of time than the DEMs allow us to resolve. SMB is dominated by iceberg calving, some melt runoff, and accumulation. Using the RACMO2. 1/ANT27 dataset of SMB up to 2011. 0  (Lenaerts et al. , 2012) , we removed the long term trend to obtain anomalies to the mean at each grid point, and converted them to a set of loading discs. The elastic response to the SMB anomalies was calculated at Palmer, and superimposed onto the time series for the best fit viscoelastic model from Fig.
Acknowledgements G. A. N. is supported by a  NERC  PhD studentship, M. A. K. is a recipient of an  Australian Research Council   Future Fellowship  (project number  FT110100207 ), and P. L. W. is a recipient of a  NERC Independent Research Fellowship  ( NE/K009958/1 ). VE-CL0V3RS was developed by V. R. B and A. B in a self-funded project. Installation of the LARISSA cGPS network was supported by  NSF  grant  OPP-ANT-0732467  to E. W. D. while data acquisition and station vitality are supported by  UNAVCO. Support of field logistics  for station installation was provided by the crew and staff aboard the USAP vessels L. M. Gould  and  N. B. Palmer ; we thank them and LARISSA colleagues for invaluable assistance. E. B. acknowledges support from the  French Space Agency (CNES)  through the TOSCA and ISIS programs (proposal numbers 282, 528 and 638).
Study population The ANRS CO3 Aquitaine Cohort is an open prospective cohort of HIV-1 infected patients followed in nine public hospitals of the Aquitaine region in Southwestern France. The cohort was initiated in 1987 and includes adults with documented HIV infection regardless of clinical stage and informed consent. Details of the cohort can be found elsewhere  [12]. The ANRS CO3 Aquitaine Cohort was approved by the French Commission Nationale de L'Informatique et des Libertés (88-84, 88-142, DR-2010-109). Participants provided written informed consent and the study is conducted in compliance with the Helsinki Declaration. The Evandro Chagas Clinical Research Institute (IPEC) has provided care to HIV-infected patients in Rio de Janeiro since 1986. An observational, longitudinal, clinical database has been maintained on patients receiving primary HIV care in the clinic since 1998.
Longitudinal data are updated regularly using outpatient and inpatient clinical documentation, laboratory testing results, and pharmacy records. Prescription of cART (drug, dates of use, and dose) is documented by the medical provider and support staff in the clinical records. Trained abstractors record all this information onto standardized forms for processing. Details of the cohort have been described elsewhere  [13]. The IPEC cohort was approved by the Evandro Chagas Clinical Research Ethics Committee (043/2010, 0032. 0. 009. 000-10). Participants provided written informed consent and the study is conducted in compliance with the Helsinki Declaration. The sample selected for this analysis included all adult patients (age ≥ 18 years) followed in each cohort from 2000 to 2008.
Signs and syndromes were considered as events if they were not reported along with other diagnoses during a specific hospitalization. Hospitalizations due to a non-morbid cause (check-ups, chemotherapy, drug withdrawal programme, and more generally Z codes of the ICD-10 classification), whatever the duration of the stay, were not considered in our definition of severe morbidity and were not included in this analysis. All events retrieved from the database were reviewed and validated by two clinicians highly experienced in the management of HIV infection, one clinician from Brazil and another from France. The lists of codes allocated to the different disease categories by each cohort were then compared and all discrepancies were discussed until a consensus was reached. Severe morbid events were classified under 22 disease categories as follows: (1) AIDS, (2) Non-AIDS malignancies, (3) In situ malignancies, (4) Cardiovascular, (5) Hepatic, (6) Digestive, (7) Psychiatric, (8) Hematological, (9) Renal,  (10)   Age from birth was updated yearly for each participant.
Although improved management of traditional cardiovascular risk factors and the use of more lipid friendlier ART regimens may have a favorable impact on the incidence of cardiovascular events, the French hospital database showed that HIV replication and immune status are independent predictors of myocardial infarction in HIV-infected individuals  [24]. Further investigations should look for optimal monitoring strategies for non-AIDS co-morbidities in individuals on and off cART both in high-and middle/low-income countries, especially among those aged 50 and above. Hepatic failure secondary to viral hepatitis was the most frequent hepatic event in our analysis. Other studies have demonstrated the increasing impact of chronic viral hepatitis and liver disease on hospital admission rates  [22, [25] [26] [27].
Acknowledgements This study was partially funded by the grant " Cooperation Franco-Bresilienne en Recherche Medicale Accord Inserm  ( Institut National de la Santé et de la Recherche Medicale )/FIOCRUZ 2010". The  ANRS C03 Aquitaine Cohort  is supported by grants from the  French Agency for AIDS and hepatitis research (ANRS)  through the  HIV Cohort Program  ( AC7 ) together with the  Bordeaux School of Public Health  ( ISPED -Bordeaux University ), Inserm  CIC-EC7  and  U897  (Bordeaux) and the  COREVIH Aquitaine (Bordeaux University Hospital ). BG and PML acknowledge funding from the  National Council of Technological and Scientific Development (CNPq)  and the  Research Funding Agency of the State of Rio de Janeiro (FAPERJ). The funding bodies had no role in the design, collection, analysis, or interpretation of data; in the writing of the manuscript; or in the decision to submit the manuscript for publication.
Sample Data came from the April to December 2011 Army STARRS All-Army Study (AAS), a deidentified representative cross-sectional survey of active duty Army personnel exclusive of soldiers in Basic Combat Training or deployed to a combat theater excluding personnel in units of fewer than 30 soldiers (representing less than 2% of all Army personnel). The 5428 respondents considered herein consist of Regular Army personnel (ie, excluding activated Army National Guard and Army Reserve) who completed a group-administered self-report questionnaire survey and agreed to have their administrative records linked to their survey responses. Written informed consent was obtained prior to data collection. Informed consent and human subjects protection procedures were approved by the Human Subjects Committees of all collaborating organizations.
Patients and study design The study was approved by the University Hospital Ethical Committee and the Committee for the Protection of Patients from Biological Risks. All participating patients gave written informed consent. A total of 30 first KT recipients were included for this study. Detailed clinical data are presented in Table  1. Blood samples were obtained from patients with the following status at the time of blood collection: (1) First kidney recipients with stable graft function treated with Belatacept (Bristol-Myers Squibb [BMS] Company, New York, NY), mycophenolate mofetil and steroids (n ¼ 13; Belatacept). We picked out patients from Phases II (n ¼ 1) and III (n ¼ 10) clinical studies cohorts (BMS) and local cohort treated after full market approval (n ¼ 2). These patients have had stable renal function (GFR) as estimated by MDRD formula, nonsignificant proteinuria and no acute rejection within the year before inclusion.
Statistics Quantitative variables are presented as means (SD) and medians with range (min-max) values, according to the distribution of the variable concerned. Qualitative values are expressed as percentages. Stable KT groups were compared at the time of inclusion. Quantitative variables were compared with unpaired t-test or Mann-Whitney, depending on the distribution of the variable concerned. Qualitative variables were compared with Fisher test or chi-square test. Biological data were analyzed with the nonparametric Mann-Whitney test (flow cytometry and qPCR data). To compare early and late B cell phenotype, we used paired t-test. A p-value < 0. 05 was considered as significant. All analyses were performed using GraphPad Prism version 5. 01 for Windows (GraphPad Software, Inc. , San Diego, CA).
Belatacept patients maintain higher proportion of transitional B cells along KT We performed a late B cell phenotype in seven patients treated with Belatacept and in two patients treated with CNI. Late blood samples were collected 20. 80 AE 0. 79 months after the initial one. The proportion of na€ ıve transitional B cells (CD24 hi CD38 hi ) was similar in both time points (N ¼ 7; p ¼ 0. 37) (Figure  4 ). In CNI patients, lower proportion of na€ ıve transitional B cells was stable (N ¼ 2; data not shown). B cell phenotype observed in stable KT recipients remained stable within almost 6 years posttransplant.
Observations and data reduction Our targets were observed with the Infrared Spectrometer And Array Camera (ISAAC,  Moorwood et al. 1998 ) mounted on the VLT/UT3 telescope. The instrument was operated in low-resolution mode with the 0. 3" slit at central wavelengths 1. 25 µm, 1. 65 µm and 2. 2 µm. This setup provides spectra with resolving powers of ∼1700, 1600, and 1500 from 1. 1-1. 4 µm (J band), 1. 42-1. 82 µm (H band), and 1. 82-2. 5 µm (K band). Nodding and small jittering of the source along the slit were performed to correct bad pixels and to subtract the sky and bias contributions. Sources at high airmasses were observed with the slit aligned with the parallactic angle to mitigate differential flux losses. We observed DENIS 1245 on April 6 and April 21, 2010. We took 6 × 120 s exposures in the J band, and 6 × 90 s exposures in the H and K bands.
We moved the star along the slit between two positions separated by 20 arcseconds following an ABBA strategy. We applied additional small offsets (5") around the two source positions between each exposure to efficiently filter out non-linear and hot-pixels at the data reduction step. We followed a similar strategy for the remaining targets. Data integration times and the number of exposures are reported in Table  1. Early-type stars were observed soon after the science target at similar airmass to ensure a proper removal of telluric features. These observations are also summarized in Table  1. Calibrations were obtained during the day following the observations: flat fields, wavelength calibration frames, and frames with a star moving along the slit in low and medium-resolution to compute the spectral curvature.
Data were reduced using the 6. 1. 3 version of the ISAAC pipeline  (Devillard et al. 1999; Silva & Peron 2004)  provided by the European Southern Observatory. The pipeline identifies pairs of sky-object frames and subtracts them. The calibration in wavelength and the slit curvature distortion were performed using exposures with the Xenon and Argon lamps. The slit curvature was modeled with a bivariate 2-d polynomial. The dispersion relation was computed by matching a Xenon and/or Argon atlas with the corrected spectra. The pipeline divides the raw images by the flat field, corrects bad-pixels and distortion, and reconstructs the combined sky-subtracted 2D spectra from a shift of the nodded images. The object flux is extracted in each spectral channel to build the final spectrum. Data on the objects and associated telluric standard stars were reduced in a similar way.
Acknowledgements. We are grateful to the  ESO  staff for their support during the preparation of the observations and their execution. We acknowledge  Emily Rice ,  Kathlyn Allers ,  Quinn Konopacky ,  Stan Metchev ,  David Lafrenière ,  Jenny Patience ,  Michael Liu ,  Tobias Schmidt ,  Andreas Seifahrt ,  Brendan Bowler ,  Zahed Wahhaj ,  Laird Close ,  Davy Kirkpatrick ,  Nadya Gorlova ,  Carlo Felice Manara , and  Catherine Slesnick  for providing the spectra of their low-gravity/young objects. We also thank  Michael Cushing ,  John Rayner , and  Ian Mc Lean  for providing an online access to their spectral librairies. This research has benefitted from the  SpeX Prism Spectral Libraries , maintained by  Adam Burgasser  at http://pono. ucsd. edu/∼adam/browndwarfs/spexprism. It has also made use of the SIMBAD database operated at  CDS, Strasbourg, France.
Gaël Chauvin ,  Anne-Marie Lagrange ,  France Allard , and  Derek Homeier  acknowledge financial support from the  French National Research Agency (ANR)  through project grant  ANR10-BLANC0504-01. This project is also supported by the  "Programme National de Physique Stellaire" (PNPS)  of  CNRS (INSU) in France , the  European Research Council  under the European Community's  Seventh Framework Program  (FP7/2007-2013 Grant Agreement no. 247060 ), and the  Lyon Institute of Origins  under grant  ANR-10-LABX-66. This work was supported by  Sonderforschungsbereich   SFB 881  " The Milky Way System " (subproject  B6 ) of the  German Research Foundation (DFG). N. Lodieu was funded by the  Ramón y Cajal  fellowship number  08-303-01-02. This research has been partially supported by the  Spanish Ministry of Economics and Competitiveness  under the project  AYA2010-19136.
Detection of somatic hypermutation This is achieved by sequencing the IGH variable region segment of a clonal population and comparing it to a database of germline sequences. If the difference accounts for more than 2% of the nucleotides, the segment is considered mutated. In fundamental studies, Damle et al and Hamblin et al have shown  80, 81  that the presence of unmutated IGH variable region genes predicts for an inferior survival in CLL. There is to the extent of our knowledge no equivalent study in myeloma. In a clinical setting, apart from diagnosis, the main reason for identifying translocations is to stratify patients and use this information to guide treatment. In myeloma, for instance, some translocations are of prognostic value, such as t(4;14)(p16;q32), and to a lesser extent t(14;16)(q32;q23) or t(14;20)(q32;q12).
Studies in CLL suggest it could be a good diagnostic tool and useful for monitoring MRD after transplant. 91 In myeloma, 133 newly diagnosed patients with a very good partial response were evaluated using a next-generation sequencing-based MRD test. This approach proved feasible (91% of patients were evaluable) and the median overall survival was proportionate to the depth of response. 90 Studies in other B-cell malignancies are encouraging,  92  but should nevertheless be confirmed in a prospective setting. The current sequencing costs for rearranged antigen-receptor genes are comparable with those of flow cytometry and PCR. Sequencing data may be complex to interpret, but the current analytic algorithms facilitate detection and quantitation of genetic events.
The units are placed on opposite sides of the SOHO spacecraft, and data can be combined to cover all directions in the sky. A complete observation of the sky is performed in roughly 24 h. One of the science objectives of SWAN is to derive the pattern of the solar wind mass flux and its variations. SWAN records full sky maps of backscattered Lyman  intensity (i. e. , interplanetary background) on a daily basis. These maps are used to determine the distribution of interplanetary hydrogen atoms  [Bertaux et al. , 1995 [Bertaux et al. , , 1997;; Quémerais et al. , 2006]. Based on comparisons between data and models of the interplanetary hydrogen distribution, the maps are used to derive the heliographic latitudinal distribution of the ionizing fluxes from the Sun. In the inner heliosphere, hydrogen atoms are ionized through charge exchange or photoionization processes.
The first gap is due to the fact that SWAN cannot look close to the Sun which is too bright. Direct sunlight on the photocathode of the intensifiers would damage the detectors permanently. Therefore, the look direction of the unit must be kept at an angle larger than 10 • from the Sun. To prevent accidental observations, the direction of the Sun is blocked by an external occultor that blocks the SWAN unit field of views. Unfortunately, grazing sunlight on the edge of the occultors also cause some straylight within 15-20 • of the solar direction. On the antisolar direction, a large portion of the sky is blocked by the SOHO spacecraft. Reflected sunlight on the spacecraft also causes some straylight within a  few degrees from the blocked portion of the sky. When data necessary for our analysis were missing because of the gaps in the SWAN maps, we have interpolated the maps using interplanetary background models.
4 AU) compared to the data. Therefore, in this model, either the ionization rate or the radiation pressure is not high enough. On the other hand, the 2009 model gives an estimate of the SOHO-MESSENGER peak intensity of 70 R, which is very close to the peak intensity in the data (80 R), deriving the corresponding column density is model dependent. The value found from the 2009 model divided by the SOHO-MESSENGER distance gives an average number density of hydrogen atoms between SOHO and MESSENGER of 2300 m -3 ± 1000 m -3. This value is based on the SWAN calibration level. If we use the MASCS-UVVS calibration level, the value of the mean density is 1640 m -3 ± 700 m -3. Saul et al. [2012]  have published values of the interplanetary hydrogen seen by IBEX-Lo. To compare to our results, one would have to assume a velocity profile.
We estimated the corrections based on solar Lyman  flux measurements at the time our observations were made. We found that the corrections were always smaller than 5 to 10% and could be neglected here. When performing the cross calibration, we found that the ratio between the two data sets was very stable, with a mean value of 1. 39 ± 0. 05. A similar result was found by  Pryor et al. [2013]. In this work, the authors scaled both data sets to a model and derived a cross-calibration ratio of 1. 3. At the present time, it is not possible to clarify this matter any further but a similar topic was discussed at length by the Fully Online Database of UV Emissions (FONDUE) working group which was sponsored by ISSI (see Cross-Calibration of Far UV Spectra of Solar System Objects and the Heliosphere, ISSI Scientific Report Series, Volume 13.
ISBN 978-1-4614-6383-2, editors E. Quémerais, M. Snow, and R. M. Bonnet, 2013). The MESSENGER-MASCS data can also be used to triangulate the position of the maximum of volume emission rate (MER) in the interplanetary medium. This maximum is aligned with the direction of the interstellar hydrogen wind. Its ecliptic longitude (J2000) is equal to 253. 2 • ± 2. 0 •. This value is very close to the one found by  Quémerais et al. [1999]  when analyzing the SWAN hydrogen cell data obtained in 1996 and 1997. This suggests that the interstellar hydrogen wind directions have been stable between 1996 and 2010. Recently,  Frisch et al. [2014]  suggested that the He interstellar wind may have been shifting in the last few decades. Our conclusion about interstellar hydrogen does not support this suggestion.
If the claim of  Frisch et al. [2014]  is correct, it will be necessary to understand why the interstellar hydrogen direction seems stable. In this work, we also find that at the time of IPH observations by MASCS in 2010, the MER is at 2. 37 ± 0. 2 AU from the Sun. This does not compare well to our current model for close to solar minimum conditions because it gives a MER-Sun distance equal to 1. 4 AU. On the other hand, the model for close to solar maximum conditions gives a distance of 2. 2 AU. This would suggest that the in-ecliptic parameters are not large enough (radiation pressure or hydrogen total ionization). This will be studied in detail in future works with the SWAN data that can be used to get the MER position from parallax values and triangulation. By comparison with models that propagate hydrogen atoms in the solar system  [Izmodenov et al.
Human mobility is a key component of large-scale spatial-transmission models of infectious diseases. Correctly modeling and quantifying human mobility is critical for improving epidemic control, but may be hindered by data incompleteness or unavailability. Here we explore the opportunity of using proxies for individual mobility to describe commuting flows and predict the diffusion of an influenza-like-illness epidemic. We consider three European countries and the corresponding commuting networks at different resolution scales, obtained from (i) official census surveys, (ii) proxy mobility data extracted from mobile phone call records, and (iii) the radiation model calibrated with census data. Metapopulation models defined on these countries and integrating the different mobility layers are compared in terms of epidemic observables.