dataesr/scientific-paragraphs-categorization huggingface dataset:
We use statistical methods like Maximum Likelihood Estimation and the Kalmogorov Smirnov test to fit the traffic data. We plot the PDF, the CDF and the fitting distributions using some functions of the statistical toolbox of MATLAB. We also plot the autocorrelation function which shows the long range dependance of the inter-arrival times. From the plots, we can see that most of the inter-arrival times are in the interval 10ms-20ms. Knowing that the mean service time of the video playbacks is 40ms, that confirms the high performance of the LTE networks. Our results can be used to analyse the quality of experience of the video streaming applications and the quality of service of the LTE networks. As future works, we plan to do the same simulations with ns-3, in order to compare the performances of the two simulators.
Comparison with other disks Over the past several years there have been multiple examples of circumstellar disks where the interpretation of radial variations of the dust properties is supported by resolved observations at mm and cm wavelengths  (Isella et al. 2010; Guilloteau et al. 2011; Trotta et al. 2013; Menu et al. 2014; Kwon et al. 2015). For example, in TW Hya,  Menu et al. (2014)  found that a radially homogeneous distribution of small and large grains (larger than ∼ 100 µm) was not a suitable representation of the observations, and a steeper Σ(R) for the larger grains was required to fit these multi-wavelength dataset. And recently  Kwon et al. (2015)  studied a sample of disks and found that those with a steep midplane density gradient generally possess a smaller value of β, indicative of dust growth and radial evolution.
We thank the referee for valuable comments. The  National Radio Astronomy Observatory  is a facility of the National Science Foundation operated under cooperative agreement by  Associated Universities, Inc. Ongoing CARMA development and operations are supported by the  National Science Foundation  under a cooperative agreement, and by the CARMA partner universities. The SMA is a joint project between the  Smithsonian Astrophysical Observatory  and the  Academia Sinica Institute of Astronomy and Astrophysics , funded by the  Smithsonian Institution  and  Academia Sinica. Part of this research was carried out at the  Jet Propulsion Laboratory, Caltech , under a contract with the  National Aeronautics and Space Administration. Facilities: CARMA, SMA,  VLA.
Methodology Data Collection The data for this study consists of two blogs and additional comments posted anonymously on the Internet by their authors (EA Spouse and Rockstar Spouse). Blogs are generally defined as frequently updated websites consisting of dated entries arranged in reverse chronological order  (Walker Rettberg, 2008). Blogs allow dialogue or co-production between authors and readers in the form of comments, while the author retains ownership of and, ultimate control over, the blog's content  (Hookway, 2008). Blogs offer an unadulterated first-person perspective and that often has a confessional quality or represents alternative voices on the subjects/topics addressed  (Hookway, 2008). The first blog is entitled 'The Human Story' and was posted using the free blogging software Live Journal under the tagline 'ea_spouse' on November 10, 2004.
Analysis The blogs were analyzed to locate the narrator's perception of the situation within a wider structural and discursive context  (McKenna, 2010). Here, blogs act as a forum through which the narrator (the blog writer) can express emotions and feelings about their lives  (Boudens, 2005; McKenna, 2007). Blogs as a narrative, not only represent things in the world; they also have an interactional function and position the writer in a web of voices and relationships with others. While a blog may describe a situation, it also introduces alternative voices, discourses and narratives. In the case of these two blogs, the writers engage with a broader context in such a way as to raise questions about injustice and exploitation in a particular aspect of organizational or social life. The blogs were analyzed thematically  (King, 1998; Riessman, 1993)  using NVIVO qualitative data management software.
The researchers independently coded the data for main sub-themes within the over-arching narrative of extreme work, and then collectively reconciled the list of themes. This process resulted in the identification of four dominant sub-themes: quality games, crunch (sustained overtime), project-based control, health issues and family conflict. These themes were then applied to the categorization and classification of the blog comments. Due to their volume, only a portion of the 4811 comments was formally coded. All of the 152 Rockstar Spouse comments were coded and approximately 10% of the EA Spouse comments were coded beginning on page 1. For the latter, coding continued until a point of saturation for the identified central themes was reached. In addition to the sub-themes listed above, the comments were also categorized as being 'supportive' or 'unsupportive' of the tenor of the respective blog.
Health Issues and Family Conflict Supporting other research, an important sub-theme in the data was the negative impact of long hours on physical and psychological health  (Burke and Cooper, 2008). EA Spouse and Rockstar Spouse document the toll paid by the development teams and these details are confirmed and expanded throughout the comment sections. Stress, burnout, depression, frustration, irritability, exhaustion, alcoholism, and suicidal tendencies were repeated themes. Rockstar Spouse criticizes the use of superficial techniques of 'stress management' saying, "[health problems] will not be ameliorated with a full time masseuse and will only worsen if no change to improve conditions take place and managers continue with their dishonesty of deadlines. " The blog authors and other commentators seem to see this weak 'welfarism' response as insulting and voice management as dishonest in their concern, particularly when management belittles and resents the use of the health system in place (i.
Location European Alps. Methods We sampled 12 individuals from each of 102 populations of R. kuepferi across the Alps, determined their ploidy levels, derived coarse-grain (100 9 100 m) environmental descriptors for all sampling sites by downscaling WorldClim maps, and calculated fine-scale environmental descriptors (2 9 2 m) from indicator values of the vegetation accompanying the sampled individuals. Both coarse and fine-scale variables were further computed for 8239 vegetation plots from across the Alps. Subsequently, we compared niche optima and breadths of diploid and tetraploid cytotypes by combining principal components analysis and kernel smoothing procedures. Comparisons were done separately for coarse and fine-grain data sets and for sympatric, allopatric and the total set of populations.
, 2013; Glennon et al. , 2014). Representing climatic conditions at an appropriate scale and incorporating non-climatic niche dimensions are hence next steps to improve analyses of niche differentiation between diploid and polyploid plants. Taking these steps is usually limited by data availability but the use of indicator values (e. g. Ellenberg et al. , 1991; Landolt et al. , 2010)  derived from the vegetation accompanying the species or cytotypes  (Felber-Girard et al. , 1996; Lenoir et al. , 2013)  offers a way to circumvent this problem. Studying the niches of taxa based on such indicator values has been facilitated with the growing availability of vegetation plot databases which provide fine-grain vegetation data over a large spatial extent (e. g. Lenoir et al. , 2012). From these databases, presence-absence information for a species of interest can be derived and indicator values of e.
, 2014). As a corollary, however, the method does not only need environmental information about the sampling sites of species, but also on the availability of environmental conditions in the background area. In addition to our sampling plots, we hence used a set of vegetation relev es from the European Alps to characterize the density of environmental conditions across the Alpine range of R. kuepferi. The relev es were taken from the Alps vegetation database  (Lenoir et al. , 2012)  and contain 8239 plots with size < 125 m 2 that were sampled at elevations between 1000 and 3400 m a. s. l. and that have a maximum of 5% of tree or tall shrub (> 2 m) cover (see  Nieto-Lugilde et al. , 2014). These vegetation relev es are georeferenced and include a complete list of vascular plant species. Hence, both full coarse-grained and finegrained environmental data values could be calculated for them in the same way as for our own R.
kuepferi sampling plots. Our subsequent comparison of the calculated niches of diploid and tetraploid cytotypes combined several approaches. First, we used the niche equivalency and similarity tests proposed by  Warren et al. (2008)  and implemented in the package 'ecospat' for R  (Broennimann et al. , 2014). Both tests rely on the niche overlap metric D  (Schoener, 1970)  which ranges from 0 (no overlap) to 1 (complete overlap). The niche equivalency test is a strict test of niche conservatism. Occurrences of both cytotypes are pooled and randomly re-split into two data sets, with the respective numbers of occurrences of the two cytotypes kept constant. Niches are considered non-equivalent if the observed D falls within the lower 5% quantile of 100 reshuffled Ds. By contrast, the niche similarity test examines whether the environmental niche of one cytotype is more (dis)similar to the niche of the other one than expected by chance.
ACKNOWLEDGEMENTS B. K. , A. D. , M. W. and S. D. were supported by the  Austrian Science fund  (project number: I 1443), E. H. , C. C. F. S. and S. K. by the  German Research Foundation  (project number  Ho 4395/1-1 ). WT received support from the  European Research Council  under the European Community's  Seventh Framework Programme   FP7/2007-2013  Grant Agreement no. 281422  (TEEMBIO). J. C. S. was supported by the  Aarhus University and Aarhus University Research Foundation  under the  AU IDEAS program  (via  Center for Informatics Research on Complexity in Ecology, CIRCE). We thank  Siegrun Ertl ,  Christian Gilli ,  Franz Hadacek  and Karl H€ ulber for help with fieldwork.
The CHER and PENTA11 studies include children who underwent planned treatment interruption after early ART and all patients showed a viral rebound. These children will be stratified according to time to viral rebound (defined as viral load over 1000 copies/mL) as 'rapid rebounders' or 'slow rebounders', with cut-off points for inclusion in the two groups based on statistical analysis and modelling of the data (Figure  3 ). To validate this predictive platform, we plan to generate new immunological, virological and transcriptomic (by RNA sequencing/Fluidigm-Biomark)  [41]  correlates/profiles of viral control in early-treated HIV-infected children (Figure  3 ). The development of mathematical models applied to retrospective data from such cohorts represents a major novel insight for the EPIICAL project.
Virological assays can provide not only a static picture of the viral reservoir, but more importantly, provide unique virological data on the evolution of the reservoir following treatment initiation and treatment interruption in large existing international cohorts. A combination of different and complementary techniques quantifying integrated HIV-1 DNA, 2-LTR circles, cell-associated RNA and low level residual viraemia and serology will be used to measure the viral reservoir to evaluate virological outcomes in PoC studies. Furthermore, immunological data together with virological data will be used to feed and refine the predictive model to identify genomic signatures related to virological control (Figure  4a ). For this purpose, a novel protocol has been developed and is discussed further in Cotugno et al.
Using this p + p measurement as a baseline we obtain the nuclear modification factor (R dAu and R A A ) of the three states combined:   2006 ) was not included in this analysis; the amount of material in the detector at that point was substantially larger than it was in the three datasets discussed here. We compare our data to model calculations of the cross section based on perturbative QCD (pQCD)  [23] , and to recent models of Υ production in d + Au and Au + Au collisions  [24] [25] [26] [27] [28] [29]. Υ (1S + 2S + 3S).
Hence, triggering thresholds are not precise in energy. The Υ trigger is required to be in coincidence with the STAR minimum bias trigger. For p + p collisions the minimum bias trigger is based on the STAR Beam-Beam Counters, while for d + Au and Au + Au it is based on the STAR Zero-Degree Calorimeters (ZDC) and the Vertex-Position Detectors (VPD). The L0-L2 combination was used for the d + Au data in 2008 and for p + p data in 2009. In the Au + Au 2010 run, an upgrade to the STAR data acquisition system allowed the processing of all the L0 triggers above the E L0-BEMC = 4. 2 GeV threshold, thus removing the need for a Level-2 trigger. Some of the key components common to all these analyses are the tracking, matching between TPC tracks and BEMC L0 and L2 clusters, and electron identification techniques.
The main differences between the three datasets are summarized as follows. For Au + Au collisions we use the charged particle multiplicity measured in the TPC in order to determine the centrality of the collision. Using a Glauber model simulation, the multiplicity classes in the collision are used to estimate the average number of participants (N part ) and number of binary collisions (N coll ). The trigger, tracking, and electron identification efficiencies in the Au + Au case were studied as a function of centrality (see Table  1 ). The presence of the underlying Au + Au event background increases the energy measured in the calorimeter towers and results in a slight increase in the trigger efficiency with increasing N part (more central collisions). Similarly, the increase in the track density in the TPC results in a decrease in the tracking efficiency which is especially noticeable at high N part.
We used the specific ionization of the tracks  in the TPC gas (dE/dx) for electron identification. In addition, the projection of the track onto the location of the BEMC shower maximum position was required to match the measured BEMC cluster position. Once a track was matched to a calorimeter cluster, the ratio of the energy of the cluster to the TPC momentum (E/p) was also used for electron identification. The combined acceptance times efficiency for detecting an Υ at mid-rapidity (| y| < 0. 5) in Au + Au taking into account all aforementioned effects was found to vary from ∼12% in peripheral collisions to ∼9% in central collisions. The cuts used in these analyses were chosen such that the tracking and electron identification efficiencies would be similar across the three datasets, allowing the systematic uncertainties to approximately cancel in the measurement of R A A.
For further detail, the techniques used in these Υ measurements were described extensively for our previous p + p measurement  [13]  based on a 7. 9 pb -1 dataset. All evaluated sources of systematic uncertainty are summarized in Table  2. An important effect in addition to those discussed in  [13]  is the change in tracking and mass resolution with increasing detector occupancy. Simulated Υ events were embedded in real data and their reconstructed line shapes were studied as a function of collision system and detector occupancy. In p + p collisions, we find a mass resolution of 1. 3% for reconstructed Υ (1S). Due to additional TPC alignment errors for the d + Au and Au + Au data the mass resolutions of the Υ (1S) increased to 2. 7% in d +Au and peripheral Au +Au collisions and 2. 9% in central collisions.
The L2 trigger condition has the effect of cutting off the lower invariant masses. This cut-off shape is parameterized in the fits using an error function. We integrate the unlike-sign invariant mass distribution in the region 8. 8-11 GeV/c 2 and subtract from the data the fit to the combinatorial, Drell-Yan, and b b background components in order to obtain the yield of Υ (1S + 2S + 3S). After accounting for effi- As discussed in the previous section, a misalignment in the TPC in the d + Au and Au + Au datasets led to a broadening of the Υ line shapes compared to the p + p dataset. This can be seen by A similar procedure is followed for the region 0. 5 < |y Υ | < 1 in p + p collisions. We combine the results to obtain the differential cross section: B ee × dσ /dy| |y|<1 = 58 ± 12(stat. + fit) +12 -11 pb.
We then recalculated both efficiency and purity (see Table  2 , Υ (1S) purity). Those variations were taken into account as additional systematics when quoting Υ (1S) results. Fig. 2 (a) shows the extracted Υ (1S + 2S + 3S) cross section for p + p and d + Au as a function of rapidity. The p + p measurements are shown as blue stars and the d + Au measurements as red circles. The p + p result in the region 0. 5 < |y Υ | < 1. 0 is displayed as a star at y = 0. 75 and also as a hollow star at y = -0. 75 to illustrate that the latter is not an independent measurement. The data from PHENIX at forward rapidity for p + p (filled blue diamonds) and d + Au (hollow red diamonds) are also shown  [35]. The cross sections in p + p are compared to an NLO pQCD calculation of Υ production in the Color Evaporation Model (CEM)  [23] , which is consistent with our data within the statistical and systematic uncertainties.
The same calculation is performed for d + Au including shadowing effects  [24]. The EPS09 set of nuclear Parton Distribution Functions (nPDF)  [36]  were used. The model is in agreement with our data except for the mid-rapidity point which is lower than the prediction. To study this observation for d + Au further, we make a closer comparison to models and to previous measurements of Υ production in p + A collisions. To focus on expected shadowing effects, we obtain the nuclear modification factor R dAu as a function of rapidity. The nuclear modification factor is defined in nucleus-nucleus collisions as R A A = 1 σ A A σ pp × 1 N coll × B ee × ( dσ A A dy ) Υ B ee × ( dσ pp dy ) Υ where the first factor accounts for the difference in inelastic cross section in p + p to d + Au or Au + Au collisions.
The second factor accounts for the average number of nucleon collisions in a d + Au or Au + Au collision as calculated by a Glauber model. The third factor accounts for the measured Υ production in p + p, d + Au or Au + Au. We used the following total inelastic cross sections:   3. Our data (red stars) are compared to CEM calculations with the uncertainty from the EPS09 nPDF shown as the shaded region. Note that this prediction for R dAu , which includes modification of the nuclear PDFs but does not include absorption, implies a modification factor of R dAu ≈ 1. 1. A calculation in Ref. [25]  explored various nPDFs (EKS98, EPS08, and nDSg) and also gave R dAu values above 1 with enhancements in the range of 5-20%. The models are in agreement with the data except in the y ∼ 0 region. An additional effect which can suppress the Υ yield is initial-state parton energy loss.
3(b). The larger suppression we observe at mid-rapidity is also consistent with the larger suppression seen in E772 for x F ∼ 0. We next turn to the measurements in Au + Au collisions. The Au + Au invariant mass spectrum is fit in 3 centrality bins: 30-60% (Fig. 4 (a)), 10-30% (Fig. 4(b )), and 0-10% (Fig. 4(c) ). As in Fig. 1  we show the fits including, in succession, combinatorial background (dashed blue line), the physics background from Drell-Yan and b b pairs (dot-dashed green line), and the Υ contribution (solid red line). The absence of the L2 trigger in the Au + Au dataset removes the cut-off effect. One can therefore see the background (modeled as the sum of two exponentials), dominated by the combinatorial component, rising at lower invariant mass. Measured cross sections are summarized in Table  4.
The gray bands in the Au + Au figure illustrate the expected signal from the p + p data scaled by the number of binary collisions. There is a clear suppression of the expected yield in Au + Au collisions. This suppression is quantified in Fig. 5 , which displays the nuclear modification factor, R A A , plotted as a function of N part with the 0-10% most-central collisions corresponding to N part = 326 ± 4. Fig. 5(a)  shows the data for all three states in the rapidity range |y| < 1, while Fig. 5(b ) is for the narrower |y| < 0. 5 range. Fig. 5 (c) shows R A A and R dAu for the ground state Υ (1S) in the range |y| < 1. 0. The data confirm that bottomonia are indeed suppressed in d + Au and in Au + Au collisions. For d + Au collisions, we find R dAu (1S + 2S + 3S) = 0. 79 ± 0. 22(d + Au stat.
) ± 0. 10(p + p stat. ) ± 0. 03(d + Au syst. ) ± 0. 09(p + p syst. ) in the range |y| < 1. We use a total inelastic cross section for p + p collisions of 42 mb, for d + Au collisions of 2. 2 b, and N coll = 7. 5 ± 0. 4 for calculating R dAu. In the same rapidity range and for the 0-10% most-central Au + Au collisions, we find R A A (1S + 2S + 3S) = 0. 49 ± 0. 13(Au + Au stat. ) ± 0. 07(p + p stat. ) ± 0. 02(Au + Au syst. ) ± 0. 06(p + p syst. ), which is ≈ 4. 5σ away from unity. The results are summarized in Table  3. In the narrower rapidity range (Fig. 5(b )), we see an indication of a lower R dAu as discussed earlier. Our data and the E772 data show a larger suppression at y ∼ 0 or x F ∼ 0 than that expected from shadowing. The level of suppression we observe for |y| < 0. 5 stays approximately constant from d +Au up to central Au +Au collisions.
The ratio R A A is used to quantify deviations of the yields in d + Au and Au + Au compared to those expected from a superposition of elementary p + p collisions. The data were taken during 2008 (d + Au), 2009 (p + p) and 2010 (Au + Au) at RHIC, and correspond to integrated luminosities of 28. 2 nb -1 , 20. 0 pb -1 , and 1. 08 nb -1 , respectively. All three datasets were taken with the same detector configuration. For this reason the data from our previous p + p result (.
Acknowledgements We thank  R. Vogt ,  M. Strickland ,  R. Rapp ,  F. Arleo , and  J. P. Lansberg  for providing us calculations in the STAR kinematic regions. We thank the  RHIC Operations Group  and  RCF at BNL , the  NERSC Center at LBNL , the  KISTI Center in Korea , and the  Open Science Grid consortium  for providing resources and support. This work was supported in part by the  Offices of NP  and  HEP  within the  U. S. DOE Office of Science , the  U. S. NSF ,  CNRS/IN2P3 ,  FAPESP-CNPq of Brazil , the  Ministry of Education and Science of the Russian Federation ,  NNSFC ,  CAS, MoST and MoE of China , the  Korean Research Foundation ,  GA  and  MSMT of the Czech Republic, FIAS of Germany, DAE ,  DST , and  CSIR of India , the  National Science Centre of Poland, National Research Foundation  ( NRF-2012004024 ), the Min-.
Also, an automatic setting of chopper parameters is possible for achieving different wavelength resolutions between 2 and 10% at will for different selected and L D. The data analysis software QtiKWS (http://iffwww. iff. kfajuelich. de/~pipich/dokuwiki/doku. php/qtikws) enables the further processing of data: the correction for the time delay between issuing the master pulse and the opening of the guide, the merging of the two similar pulses recorded in the TOF window, the conversion to real time scale (Fig. 6 ), the splitting into an appropriate number of time slots for reaching the Á/ aim (Fig. 6a ) and the conversion of time scale into wavelength scale (Fig. 6b ). Finally, the typical SANS data reduction procedure is applied to the data: the correction for empty beam or empty cell, the detector sensitivity and electronic noise, and the calibration in absolute units using standard samples  (Radulescu et al.