dataesr/scientific-paragraphs-categorization huggingface dataset:
CONCLUSION We used models of stellar atmospheres to synthesize stellar populations in six GGCs and compared our results to high-resolution spectroscopic and deep photometric data from the literature. A good agreement was reached for the old clusters observed spectroscopically at a resolution F W HM ≥ 5 Å , in a wide spectral range ∆λ ≥ 2000 Å and having signal-to-noise S/N > 100. ACKNOWLEDGMENTS. We acknowledge attribution of the Russian Federal Basic Research regional grant number 14-02-96501-r-ug-a which however was not received because of the Karachai-Chekessian republic. SVV acknowledges a grant RFBR13-02-00351. We acknowledge the usage of the SIMBAD database operated at the CDS (Strasbourg, France), and Google. We thank organisers of the conference "Modern stellar astronomy", where this talk was presented in 2014.
For evaluation of the recruitment kinetics, fluorescence intensities of the irradiated region were corrected for total nuclear loss of fluorescence over the time course and normalized to the pre-irradiation value. Data from microirradiation of individual cells obtained in several independent experiments performed on different days were averaged, analyzed and displayed using PRISM software. Images of fixed cells were recorded with the same microscope. For immunofluorescence experiments, irradiation was carried out at 800 nm at X2 zoom, on multiple cell fields (tile scan 3 × 3); the laser line step was set up to 7 and the total irradiation time was 10 s. Images of fixed cells were recorded with the same microscope. Fluorescence recovery after photobleaching (FRAP) experiments were performed with the Ar-laser line (GFP tag) or Ne-laser line (mCherry tag) at 100% intensity.
A single optical section of a cell nucleus was acquired at 3× zoom. Fifteen iterations were used for the bleach pulse on a strip area (5 × 20 m). Fluorescence recovery was monitored using the same laser with 0. 4% laser intensity (GFP tag) or 1% intensity (mCherry tag) to avoid bleaching during the time laps acquisition. Typically 20 images with an interval of 487 ms were taken before the bleach and during 50 or 100 s after. Fluorescence intensities of the photo-bleached region, the total nuclear region and the background outside the nucleus were measured at each time point using the 'mean intensity' analysis function of the Zeiss software. For the quantitative evaluation of the fluorescence recovery, background value was first subtracted from raw mean fluorescence data series. Then the fluorescence signal measured in a region of interest normalized to the change in total fluorescence was determined as previously described  (48).
Of note, full-length endogenous SAF-A was co-precipitated with SAF-A RDB. Among the coprecipitated proteins, FUS/TLS and TAF15/TAFII68 were chosen for further analysis. First, results of the mass-spectrometry analysis were evaluated by western blotting after reciprocal immunoprecipitation of the SAF-A and FUS proteins. As shown in Figure  3B  and C , both FUS and TAF15 were coprecipitated with the SAF-A RBD domain, together with endogenous fulllength SAF-A. In addition, SAF-A and TAF15 were coprecipitated with FUS, thus validating results of the massspectrometry analysis and suggesting a tripartite complex of these proteins in cell extracts. Notably, the interaction between SAF-A, FUS and TAF15 with the SAF-A RBD was resistant to RNase A and DNAse I treatments (data not shown). Second, in nuclei of HT1080 cells stably expressing an FUS GFP fusion, FUS showed a rapid recruitment at damage sites followed by an exclusion phase, mimicking the biphasic dynamic observed with SAF-A (Figure  3D  and Supplementary Movie 3).
ACKNOWLEDGMENTS We are indebted to  P. R. Hamann  ( Wyeth Research ) for the gift of calicheamicin ␥ 1, to  Pr B. Hazra  ( Jadavpur University, Calcutta, India ) for the gift of Diospyrin, to  Dr S. H. Leppla  ( National Institutes of Health, Bethesda, MD, USA ) for the gift of the S9. 6 antibody and to  Dr G. Giglia-Mari  ( IPBS, Toulouse, France ) for the gift of anti-RNA Pol II antibody. P. Calsou is a scientist from  INSERM, France.
Data analyses Variation partitioning was employed, using the ''varpart'' function in the ''vegan'' package  (Oksanen et al. 2010)  of the R software environment (R Development Core Team 2012) in order to decompose the variation of the environmental variables into the two controlled factors (latitude and season) and their shared variation. Variation partitioning uses a series of partial regression analyses to estimate how much variation of the response variable is explained by a set of predictors, while controlling for another set  (Legendre and Legendre 1998 ). Variation partitioning led to the following four fractions: a unique effect of latitude (independent of season); a unique effect of season; a joint or shared effect of latitude and season; and unexplained variation. The different partitions explained by the predictors were evaluated by ANOVA-like permutation tests, which have fewer assumptions than parametric methods, using the function ''anova.
rda'' from the vegan package  (Peres-Neto et al. 2006 , Oksanen et al. 2010 ). Spearman's correlation analysis (r S ) was used to examine the relationships between the environmental variables and latitude. A principal components analysis (PCA) was conducted using the ''rda'' function of the vegan package to summarize the relationships among the water feature variables. The ''envit'' function  (Oksanen et al. 2010 ) was used to project month (categorical factor), latitude, percentage of agricultural use, and basin area as supplementary variables in the PCA biplot to help interpretation. Partial redundancy analysis (partial RDA), which is a multivariate analogue of partial linear regression  (Borcard et al. 2011) , helped to explain the effects of latitude on the set of water feature variables, after accounting for season (months).
For all of these analyses, conductivity and basin area were log 10 (x) transformed, while all the concentration variables (except O 2 ) were log 10 (x þ 1) transformed because in this way, the linearity and homoscedasticity assumptions of statistical analyses (linear regression analyses and variation partitioning) were better satisfied. We used generalized additive models (GAMs) to test for site effects in the relationship between the standard length (dependent variable) and age (continuous independent variable) of the mosquitofish, i. e. , to find out whether site-specific growth models were necessary. GAMs were applied using the R package ''gam''  (Hastie 2011) , separately for female and male data because of the obvious sexual size dimorphism (see Appendix: Figs. A5  and A6 ). GAMs are a semi-parametric extension of generalized linear models, which allow for highly non-linear relationships (such as, for example, in seasonal growth) between the response and the predictors by using smoothing functions whose complexity is automatically controlled  (Hastie and Tibshirani 1990).
We used the Akaike information criteria (AIC) and likelihood ratio tests to compare the fit of the models (see, e. g. ,  Crawley 2007). The model that indicated a site effect on growth had the best fit (Table  4 ) and showed significant effects of site in the relationship between size and age. Therefore, we additionally modelled fish growth separately for each site along the latitudinal gradient. The FSA package (Ogle 2011) of the R environment was used to estimate  Somers' (1988)  seasonal version of the von Bertalanffy growth curve: L t ¼ L' 1 À exp À Kðt À t 0 Þ À ðCK=2pÞsin 2pðt À t S Þ þ ðCK=2pÞsin 2pðt 0 À t S Þ where L t is the expected or average length at age or time t; L ' is the asymptote for average length; K is a measure of the exponential rate of approach to the asymptotic length L ' (units are yr À1 ); t 0 is the theoretical age (generally negative) at which the average length would be zero; C modulates the amplitude of the growth oscillations; and t S is the time between time 0 and the start of the convex portion of the first sinusoidal growth oscillation (i.
e. , the inflection point because, in general, it did not fit well to the male data, due to a more limited range of ages for males. To avoid convergence and computation problems, and to improve the estimation accuracy of the Somers' model, we used the ''nls2'' function of the ''nls2'' package  (Grothendieck 2010) , with a wide range of plausible values as starting values. We estimated the R 2 of the nonlinear models with function ''Rsq'' of package ''qpcR''  (Spiess and Ritz 2012). The growth performance index (U') was also calculated from the growth parameter estimates as it facilitates the comparison of growth rates because K and L ' estimates are often negatively correlated  (Pauly and Munro 1984) : U 0 ¼ log 10 K þ 2log 10 L ' : Finally, specific growth rates (GR) in winter (from February to March) were calculated with the usual formula: GR ¼ 100 log e ðL 2 =L 1 Þ.
The points are the observed data and the lines are the fitted Somers' (1988) seasonal growth models. Age estimated from scales was converted to fractional age by considering the sampling date and the estimated birth date of the cohort. The numbers in the top-left corner are the site codes (see Table  1 ), from the northernmost (Site 1) to the southernmost (Site 10). The parameter estimates of  Somers' (1988)  model are given in Table  4. this is often not the case, particularly at large spatial scales and in lowlands  (Hawkins et al. 1997 , Lewis et al. 2000). Hawkins et al. (1997)  in a study of temperate streams across a latitudinal gradient of 68, which was very similar to our gradient, showed that water temperatures were barely related to latitude and in fact, were more related to differences in geomorphology and hydrology.
ACKNOWLEDGMENTS We thank  Carles Alcaraz ,  Lluı ´s Benejam ,  Josep Benito ,  Luciano Santos  and  Elena Herna  ´ndez for field and laboratory assistance and  David Reznick  and anonymous reviewers for their helpful comments on the manuscript. GCC received support from  Josep Carmona  and  Joana Catot , and benefited from a  doctoral fellowship  ( BR2010/10 ) from the  University of Girona  during the preparation of the manuscript. Financial support was provided by the  Spanish Ministry of Economy and Competitiveness  (projects  CGL2009-12877-C02-01 ,  CGL2013-43822-R  and  CSD2009-00065 ) and the  University of Girona  (project  SING12/09 ).
Ultrasound imaging procedure All images were acquired using a research ultrasound system. This scanner is composed of an electronic module for ultrasound emission and reception (V1, Verasonics, USA), a linear array transducer with a central frequency of 15 MHz (L15-128, 128 elements, 0. 1 mm pitch, Vermon, France) and a bi-CPU computer workstation on which custom MATLAB R2012 scripts (MathWorks Inc. , USA) are used to generate the pulse wave, to reconstruct all images (including beamforming and filtering steps) and to control the electrical stimulator. Functional ultrasound imaging was performed at day 0, 2 and 7 days (n = 4) after the initial surgery. Rats were anesthetized with isoflurane (1. 25% in 100% O 2 , 0. 5 L/min, Axience) inhaled through a mask covering the mouth and nose. All physiological parameters where monitored during the imaging sessions as described in the previous paragraph.
The stereotaxic frame and the probe were placed on an antivibratory table to minimize external sources of tissue vibration. No contrast agents were used. The ultrasound probe was oriented in the coronal plane above the brain and aligned to the region of interest using a piezoelectric linear stage (M403. 4DG, Physik Instrumente GmbH & Co. KG, Germany). The acoustic coupling was ensured by isotonic gel (Uni'Gel US, Aspet Inmed, USA) applied between the agarose and the probe. A single μ-Doppler image of the brain microvasculature in angiogram mode was obtained in 500 ms including 400 ms dedicated to data acquisition and 100 ms for data transfer to the computer. During the first 400 ms, a set of 200 ultrasonic images was acquired at a sampling frequency of 500 Hz (1 image in 2 ms). Each 2 ms image is a compound image reconstructed from 15 tilted plane wave emissions with angles varying from -7°to 7°with a 1°step.
Electrical stimulation Electrical stimulus pulses (200 μs pulse width, 1 mA intensity, 5 Hz repetition frequency) were generated using a microcontroller (Uno, Arduino, Italia) controlled by MATLAB and delivered using a constant current isolator (DS3, Digitimer Ltd. , U. K. ) to one forepaw using 2 needle-electrodes (Biopac Systems, Inc. , USA) inserted under the palmar skin between digits two and four. For functional imaging, each trial consisted of a 35 s pre-stimulus baseline period followed by a stimulus of 25 (5 s), 10 (2 s), 5 (1 s) or 1 pulse(s) and a post-stimulus period for a total duration of 50 s. The minimum time interval between two trials was 1 min. Five to ten trials were repeated for each type of stimulus during an imaging session.
Extracellular recordings On one animal, we measured the extracellular response evoked in forelimb somatosensory cortex (S1FL) for each stimulation paradigm. A 1 mm 2 cranial window was performed on the thinned skull over the S1FL. A quartz-insulated platinum-tungsten electrode (2 to 5 MΩ) was inserted into the cortical tissue (750 μm deep) using a Eckhorn mini-matrix microdrive system (Thomas Recordings). The electrode is thin (60 μm shaft; 10 μm tip diameter), but strong enough to penetrate the dura, thus reducing the damage to the neural tissue. Evoked FP (eFP) signals were acquired at a 1 KHz sampling rate without filtering, amplified, digitized with the aid of CED hardware and Spike 2 software (version 7, Cambridge Electronic Design). Electrical forelimb stimulation did introduce a short, high frequency deflection into the data, such that the data surrounding stimulation onset between -1 and 2 ms were discarded.
, 2010). Fig. 3B  shows a single μ-Doppler frame from a functional movie. Images were recorded 1 mm anterior from bregma, a coronal plane that comprises the forelimb sensorimotor cortex according to rat stereotaxic atlas  (Paxinos et al. , 1985). Signal in blood vessel is clearly detected in both cortical and subcortical areas. Fig. 3C  shows the averaged temporal profile of the CBV HRF pooling the results from the 4 animals, recorded at days 2 and 7 after the surgery with 5 trials per imaging session, so a total of 40 functional movies. In the supplementary material, a movie of a typical functional ultrasound imaging dataset is shown. We emphasized that this movie corresponds to only one forepaw stimulation (5 s duration) without averaging. The hemodynamic response associated with a single trial stimulus is easily detected by this technique.
We observed a peak amplitude of ~0. 45-0. 50 mV that occurred ~15-20 ms after an electrical stimulation. The amplitude was measured between the first positive peak and the negative peak of the trace (data not shown). Then, we calculated the ΣFP, that is, the product of eFP amplitude, stimulus rate and stimulus duration to better quantify the total FP response. This parameter is proportional to the number of pulses, as expected from the literature (data not shown). Fig. 4F  represents a plot of the ΣFP in function of the CBV increase and shows that the evolution is non-linear. We fitted this curve by a power law with a R 2 coefficient of 0. 97. As previously described by many groups, we observed a strong temporal shift between neural and μ-Doppler hemodynamic responses acting like a low pass filter, smearing out changes in the local electrical activity.
Quantitative hemodynamic parameters in the cortical arterioles and venules All data presented previously are extracted from the power Doppler signal that quantifies the total blood volume. But μ-Doppler is also suitable to assess the amount of blood flowing up or down based on a quantitative spectral separation of the Doppler signal. A typical Doppler spectrum of the cortical vasculature (averaged on a small 10 × 10 pixel ROI) is presented in Fig. 6A. The signal is composed of a positive (right) and a negative (left) signal that are proportional to the number of RBCs flowing toward and away from the transducer, respectively. As observed in Fig. 6A , very low frequencies were eliminated by a high pass filter (gray bar) with a 30 Hz cutoff frequency that was used to remove the noise coming from tissue motion and animal breathing.
Acknowledgements We thank Alexander Khodjamirian, Ulrick Egede, Thorsten Feldmann, Dirk Seidel, Nicola Serra, David Straub, Danny van Dyk, Roman Zwicky and Tobias Hurth for useful discussions. J. V. is funded by the Deutsche Forschungsgemeinschaft (DFG) within research unit FOR 1873 (QFET). J. M. and L. H. acknowledge support from FPA2011-25948, SGR2009-00894.
Because these quantities cannot be assessed via conventional medical imaging, a natural approach is to compute the wall tension and set a rupture threshold. Few studies consider the coupled fluid-structure interaction (FSI) problem, where the flow equations for blood are solved together with the structural equations for the tissue. 5 The problem is the lack of data on mechanical properties of cerebral arteries and aneurysms; most of the studies based on an FSI 6-10 framework do not use experimental mechanical behavior of the aneurysm wall as input. A few exceptions exist for abdominal aorta aneurysms  11, 12  but not for intracranial aneurysms until recently when, in a study by Costalat et al,  13  the aneurysm wall properties were characterized and a classification of aneurysm wall behavior was carried out.
Numeric Method Aneurysmal Geometry. Aneurysm geometry was obtained from 3D rotational angiography. Using dedicated software ScanIP (Simpleware, Exeter, United Kingdom), the aneurysmal geometries were cleaned up by keeping only the aneurysms and the parent vessels to reduce the region of interest. A low-pass filter was applied on the geometries to reduce  noise-to-signal ratio. The results were exported as stereolithography files to proceed to numeric analysis. Simulation Parameters. The flow boundary conditions imposed were obtained from specific patient examinations by using phasecontrast MR imaging for each aneurysm location (3T Skyra; Siemens, Erlangen, Germany). The velocity profiles were considered as uniform. Outlet pressure was computed by computational fluid dynamics and used as boundary conditions at the outlet of the computational domain.
49, specific mass s ϭ 2300 kg/m 3 , and thickness e pa ϭ 0. 6 mm. 24, 26 The thickness of the aneurysm wall is e ϭ 0. 38 mm. A linear model was used for the arterial wall because the deformations are small enough in all cases (Ͻ5%) to stay in the small deformation theory. Furthermore, the edge nodes of the arterial extremities are taken away from the displacement in the longitudinal direction. FSI Computations. Computations were performed by using Workench version 13 (ANSYS, Canonsburg, Pennsylvania). The fluid motion equations were solved with the software CFX, which uses the finite volume approach and the Newton-Raphson method for solving the subsequent nonlinear system. For the structural part, Mechanical software employed the finite-element method and the Newton-Raphson algorithm. The wall pressure resulting from the fluid was imported as boundary conditions in the structural analysis while wall displacement calculated by the structure solver was imported as a boundary condition for the fluid solver; this procedure was carried out in an iterative manner within each time-step.
ACKNOWLEDGMENTS The authors thank  Philips Healthcare Inc  for the financial support and  ANSYS Inc  for their technical support. The authors are also grateful to  Simpleware Inc. for providing the software Scan IP and for their technical support. The authors also thank the labex  NUMEV  for the financial support. Disclosures:  Simon Mendez-UNRELATED : Grants/Grants Pending:  French National Agency for Research,* OSEO ,* Comments: Grants from  French institution for Simulation of Flows with Red Blood Cells  (unrelated to the present work). Jean-Paul Lejeune-UNRELATED: Travel/Accommodations/Meeting Expenses Unrelated to Activities Listed:  B. Braun Company , Comments: Travel and accommodations expenses related to congresses and meetings of neurosurgery in France. Vincent Costalat-UNRELATED: Consultancy: ev3, Codman, Stryker, Balt; Payment for Lectures (including service on speakers bureaus): Stryker, Balt; Payment for Development of Educational Presentations: Covidien; Travel/Accommodations/Meeting Expenses Unrelated to Activities Listed: Stryker, Codman, Balt, MicroVention.
Senegal; 40 Institut de Recherche pour le Developpement (IRD), Dakar, Senegal; 41 Agincourt HDSS, South Africa; 42  Background: Mortality from non-communicable diseases (NCDs) is a major global issue, as other categories of mortality have diminished and life expectancy has increased. The World Health Organization's Member States have called for a 25% reduction in premature NCD mortality by 2025, which can only be achieved by substantial reductions in risk factors and improvements in the management of chronic conditions. A high burden of NCD mortality among much older people, who have survived other hazards, is inevitable. The INDEPTH Network collects detailed individual data within defined Health and Demographic Surveillance sites. By registering deaths and carrying out verbal autopsies to determine cause of death across many such sites, using standardised methods, the Network seeks to generate population-based mortality statistics that are not otherwise available.
Objective: To describe patterns of adult NCD mortality from INDEPTH Network sites across Africa and Asia, according to the WHO 2012 verbal autopsy (VA) cause categories, with separate consideration of premature (15Á64 years) and older (65' years) NCD mortality. Design: All adult deaths at INDEPTH sites are routinely registered and followed up with VA interviews. For this study, VA archives were transformed into the WHO 2012 VA standard format and processed using the InterVA-4 model to assign cause of death. Routine surveillance data also provide person-time denominators for mortality rates. Results: A total of 80,726 adult (over 15 years) deaths were documented over 7,423,497 person-years of observation. NCDs were attributed as the cause for 35. 6% of these deaths. Slightly less than half of adult NCD deaths occurred in the 15Á64 age group.
There has been much written about epidemics of NCD morbidity and mortality globally, and particularly in lowand middle-income countries  (5). While it is certainly true that there are many more NCD deaths now than there have been previously, it is critical to understand the medical, social, and demographic drivers of these changes, in addition to trends in specific risk factors, diseases, and health systems responses. This is important in terms of positioning the burden of NCDs appropriately in future development agendas  (6). The INDEPTH Network works with Health and Demographic Surveillance sites (HDSS) across Africa and Asia, which each follow circumscribed populations on a longitudinal basis. Core data collected include person-time at risk, together with deaths and, by means of verbal autopsy (VA), assessment of cause of death  (7).
Methods The overall INDEPTH dataset  (9)  from which these adult NCD mortality analyses are drawn is described in detail elsewhere  (8). Across the 22 participating sites (10Á31), there was documentation on 80,726 deaths in 7,423,497 person-years of observation for people aged 15 and over. VA interviews were successfully completed on 72,330 (89. 6%) of the deaths that occurred. A summary of the detailed methods used in common for this series of multisite papers is shown in Box 1. NCD mortality was defined as neoplasms, metabolic, cardiovascular, respiratory, abdominal, neurological and other NCDs, corresponding to chapters in WHO 2012 VA standard. Box 1. Summary of methodology based on the detailed description in the introductory paper (8).