dataesr/scientific-paragraphs-categorization huggingface dataset:
In the recent vehicle routing literature there is an increasing number of successful applications of hybrid metaheuristics  Gendreau et al (2008). The specific area of applying hybrid metaheuristics to dynamic and stochastic vehicle routing problems has been examined in  Ritzinger and Puchinger (2013). According to these developments, we present a DP algorithm for the multiple vehicle DARP which is able to solve small instances of the benchmark data set to optimality. Due to memory constraints we adapt this algorithm to a restricted dynamic programming heuristic, able to solve instances with more requests in short computational time. As shown in the literature, Large Neighborhood Search (LNS) is a promising concept to solve routing problems in general  (Pisinger and Ropke (2010) ), pickup and delivery problem with time windows  (Ropke and Pisinger (2006) ,  Bent and Hentenryck (2006) ) and dial-a-ride problems  (Parragh and Schmid (2013) ), we propose a hybrid heuristic which integrates the dynamic programming based algorithms into a LNS framework.
Computational Results All of the developed algorithms have been implemented in Java 7 and the tests were completed on a Intel Xeon 2. 4 GHz with 8GB of RAM. The algorithms were tested on benchmark data sets introduced by  Cordeau and Laporte (2003)  and  Ropke et al (2007) , which contain randomly generated Euclidean DARP instances. There are three different data sets: a-instances, b-instances and prinstances. The a-data set includes instances with up to 8 vehicles and up to 96 requests. At each node, a patient can be loaded or unloaded with a service time of 1 and the maximum user ride time is 30 minutes. The maximum capacity of the vehicles is limited to 3 and the time windows are tight with a range of 15 minutes. In the b-data set the maximum capacity is up to 6 and the maximum user ride time is 45 minutes.
RNA ISOLATION AND QUANTITATIVE REAL-TIME PCR Total RNA from 400 μl protoplast solution was extracted with TRI reagent (Ambion) and treated with DNase I (Macherey-Nagel) following the suppliers' protocols. Poly A-tailed RNA (1 μg) was converted to cDNA using the RevertAid reverse transcriptase (Fermentas) and oligo-dT primers. qRT-PCR reactions were performed in triplicates with the Maxtra SYBR Green Master Mix (Fermentas) and run on a Biorad iCycler according to the manufacturer's instructions. The primers used for the qRT-PCR are presented in Supplementary Table  S1. Relative gene expression was determined with a serial cDNA dilution standard curve. The actin transcript was used as an internal control in all experiments. Data was processed with the iQ software (Biorad)  (Zheng et al. , 2014).
Single profession The selection of programmes for participation was a challenge during the data collection because of ambiguous information from websites, foundations, and hospitals about current support-and rehabilitation programmes around the country. In total, eleven programmes fulfilled the inclusion criteria, meaning all cancer rehabilitation programmes in Sweden besides public healthcare clinics were covered at the point of the study, in the first half of 2011. All the programmes were secured to be anonymous. None of the programme representatives reported organisational discomfort due to participation or member defection as a result. In a recently published study  [22] , it was reported that only two cancer clinics in Sweden focus on cancer rehabilitation. In addition, two smaller teams provide some rehabilitation of cancer patients.
The need for such an evaluation is obvious as there is an imminent need for more cancer rehabilitation programmes in Sweden as in the rest of Europe, and it is important to find out what is presently viable or not in order to plan ahead. When a follow-up of the cancer support and rehabilitation programmes was performed in 2013, about two years after data were collected in the present study, we discovered that some of the programmes had discontinued. These programmes could be seen as vulnerable, led by enthusiasts and person-linked. Quality improvement as well as representative, educated peer-support linked to patient associations and foundations may have contributed to the success and continuity of such programmes. Their discontinuation made it problematic to further compare and evaluate the cancer support and rehabilitation programmes found in this study.
To make a continuous output dataset, the first six hours of each daily run were discarded as spinup. Sea surface temperature was provided by the US Navy GODAE high-resolution SST, (see http://www. usgodae. org/ftp/outgoing/fnmoc/models/ghrsst/docs/ghrsst_doc. txt) updated every six hours and interpolated between updates. Most of these configuration choices were the same as used for California in  Angevine et al. (2012). References for all WRF options can be found in  Skamarock et al. (2008). We used a version of the FLEXPART Lagrangian particle dispersion model  (Stohl et al. , 2005)  modified to use WRF output  (Brioude et al. , 2013a). FLEXPART uses the same grid spacing as in WRF. FLEXPART solves turbulent motion in a Lagrangian framework using first-order Langevin equations. The turbulent motion is stochastic and parameterized using the Hanna scheme.
The horizontal grid corresponds to that used for the driving WRF simulations. Particles are grouped into six age classes on output, with maximum ages of  3, 6, 12, 24, 48, and 120 h. Approximately 1. 8 million particles were emitted each day of the simulation. No chemical transformation or deposition was simulated. The spatial and temporal pattern of emissions is that of carbon monoxide (CO) specified according the US EPA 2011 National Emission Inventory, version 1, available as of 8 November 2013 (http: //www. epa. gov/ttn/chief/net/2011inventory. html#inventorydoc). Gridded (4 km resolution), hourly emissions for a July average weekday in 2011 have been derived from this inventory, and are publically available at the WRF/Chem data site: ftp://aftp. fsl. noaa. gov/divisions/taq/emissions_data_2011/.
Specific details on the files and datasets used for spatial and temporal partitioning are supplied in the readme. txt file at the data site. Because the map projection and domain used in the WRF and FLEXPART simulations is chosen to overlap with the US EPA emissions grid, hourly emissions from the 4 km NEI inventory are simply combined together within the 12 km grid resolution used here. Details of the emissions are not directly relevant here, since all runs use Figures the same emissions and results are normalized. When comparing with observed CO, it must be kept in mind that there are a number of CO sources not accounted for in these simulations. These include biomass burning, class-3 commercial marine vessels, and oxidation of methane and volatile organic compounds.
Meteorological evaluation Here we present some evaluation of the performance of each of the WRF configurations. Our goal is to establish that each of the runs has reasonable and comparable performance and therefore that each is a suitable ensemble member. We do not intend to comprehensively evaluate each run in this context. Evaluation of specific processes such as vertical transport by clouds is reserved for future analyses. Table  2  presents a statistical comparison of each model run to data from all 19 flights of the NOAA WP3 aircraft during SENEX. All data below 1000 m a. s. l. are used, that is, data in the daytime boundary layer and the nighttime residual layer. All the runs produce statistics in the range usually considered in the literature to be "good agreement". While small differences may be statistically significant with such a large dataset, we do not consider the differences to be of practical significance.
With every bloodborne disease, these epidemiological variables depend on how frequently individuals undergo medical procedures and the risk of acquiring HCV in each case. In our study, 1 we used data to estimate the frequencies of undergoing medical procedures and assumed that these frequencies did not change substantially in the short term; we challenged this assumption in a field study of frequent injectors in a rural cohort. Advanced age was not a feature of frequent injectors; median age was 32 years (IQR 15-45) at baseline. A follow-up study showed that they.
aureus growth, in strains expressing, or not, SprD and/or RNAIII. The amounts of Sbi proteins are provided in arbitrary units (AU) and were calculated relative to the quantity of total protein amounts per tracks, evidenced by Coomassie staining in Supplementary Figure  S5A. The graphs indicate the Sbi protein levels in wt (grey squares), ÁsprD (triangles), ÁrnaIII (empty circles) and ÁsprD-DrnaIII (filled circles) S. aureus strains. The data are representative of at least three independent experiments. The growth curve of strain wt is presented. (D) Expression levels of the Sbi protein (grey squares), RNAIII (circles) and SprD (triangles) in S. aureus strain wt during growth. Quantifications of the Sbi protein was performed as for panel C. The amounts of RNAIII (circles) and SprD (triangles) are shown in arbitrary units (AU) and were calculated relative to the 5S rRNA.
(C) Quantifications of the Sbi protein levels, during S. aureus growth, in strains expressing, or not, SprD and/or RNAIII. The amounts of Sbi proteins are provided in arbitrary units (AU) and were calculated relative to the quantity of total protein amounts per tracks, evidenced by Coomassie staining in Supplementary FigureS5A. The graphs indicate the Sbi protein levels in wt (grey squares), ÁsprD (triangles), ÁrnaIII (empty circles) and ÁsprD-DrnaIII (filled circles) S. aureus strains. The data are representative of at least three independent experiments. The growth curve of strain wt is presented. (D) Expression levels of the Sbi protein (grey squares), RNAIII (circles) and SprD (triangles) in S. aureus strain wt during growth. Quantifications of the Sbi protein was performed as for panel C.
The ortholog cluster multiple alignment of the Hfq proteins of several Clostridia and various Gram-positive or Gram-negative model species (http://mbgd. genome. ad. jp) shows that there is an extra amino acid at the Sm1-Sm2 junction only in Cd-Hfq (NTV in Ec-Hfq and DNRQ in Cd-Hfq) (Fig. 1 ). The model of Cd-Hfq protein based on the known structure of Ec-Hfq (Protein Data Bank entry 1HK9) (Swiss-Model at http://expasy. org) shows a different orientation of the loop that could propagate along the β3 and β4 sheets and thus alter the interaction of the monomers in the hexameric form of Hfq (data not shown) and affect the stability of the Cd-Hfq hexamer.
Protein purification and band-shift assay Ec-HfqHis6 and Cd-HfqHis6 were overexpressed and purified in parallel as previously described  (Ziolkowska et al. 2006). Templates for the synthesis of the different sRNAs were obtained by PCR amplification using the primers described in Supplemental Table  S2. Band-shift assays were performed as in  Folichon et al. (2005)  with Hfq concentration expressed on the basis of the hexamer form. The radioactivity signal above the level of the free RNA was counted as retarded RNA on the gel. Data were analyzed and fitted to the Hill equation using Kaleidagraph and the K 1/2 (half saturation values) were derived from the fit of the data.
ACKNOWLEDGMENTS This work was supported by the  Centre National de la Recherche Scientifique  ( UPR9073 ; now FRE3630),  University Paris-Diderot ,  Agence Nationale de la Recherche  (asSUPYCO,  ANR-12-BSV6-0007-03 ), and the " Initiative d'Excellence" program  from the  French State  (Grant " DYNAMO ,"  ANR-11-LABX-0011 ). We thank  P. Mandin  for providing strains. We are indebted to  Evelyn Sauer  for comments and suggestions and  O. Soutourina ,  I. Verstraete , and  J. Plumbridge  for discussions and critical reading of the manuscript. J. M. Desfontaines contributed to this work as an undergraduate student.
ACKNOWLEDGEMENTS We thank  Cédric Masson  for the purification of AlbC variants,  Robert Thai  for helpful advice about mass spectrometry, and  Bertrand Czarny  for use of the Beta-imager. We thank  Fabrice Beau  for useful discussions about enzymatic analyses. We are grateful to  Emmanuelle Schmitt  and  Yves Mechulam  for helpful discussions about aminoacyl-tRNA synthetases.
Acknowledgements We thank  Sadek Chetouani  for assistance in purifying the β-glucosidase. Thanks are due to  Dr C Cazevieille  and  C Sanchez  ( Centre Régional d'Imagerie Cellulaire, Université Montpellier I, Montpellier, France ) for helpful assistance in TEM. Thanks are also due to  J-M Lago  from  Carl Zeiss Microscopy  for hepful assistance in spectral imaging and to  Dr M Kelly  ( UMR SPO ) for reviewing the English language.
METHODS Enrollment of patients. Patients were prospectively and randomly enrolled from November 2010 to November 2012 in the liver unit of the University Hospital of Nice, France. Follow-up was conducted until April 2013. Nice is located on the French Riviera and has a Mediterranean climate. Seasonality (summer/autumn vs. winter/spring) has been taken into account in the analysis of data comparing the groups of patients with and without infection. This clinical study was performed according to the declaration of Helsinki, and all participants gave their written informed consent. In the case of encephalopathy, the family was asked for consent, or consent was obtained after resolution of encephalopathy. The main inclusion criterion was hospitalization with cirrhosis, irrespective of the underlying etiology.
The diagnosis of cirrhosis was made from a liver biopsy in compensated cirrhosis or from clinico-biological criteria in patients with decompensated cirrhosis. For each patient, we collected baseline clinical data including age, gender, body mass index (BMI), an etiology of cirrhosis, the presence and the grade of ascites, and encephalopathy, past medical history, drug history, and noted details of previous hospitalizations within the preceding 2 months. Biological data included alanine amino transferase (ALT), total serum bilirubin, albumin, calcium, phosphorus, creatinine, C-reactive protein (CRP), and the prothrombin index, factor V. All these parameters were measured with standard techniques. A community-acquired infection was the cause of admission for most of the patients included in the group of infected cirrhotic patients.
RESULTS General characteristics of the patients. Inclusion of patients was conducted prospectively by a clinical fellow (M. T. ) working only part time (20% of her working time), because her availability depended on external duties without any link to the present study. During the 2 years of the study, patient recruitment by M. T. was performed during her periods of availability, at which time 472 cirrhotic patients were hospitalized in our unit (including the 88 patients reported in our study, i. e. , 18. 6% of the total number of hospitalized patients). Among the 472 hospitalized patients, 219 patients had an infection as determined by our inclusion criteria (i. e. , 46% of the total number of hospitalized patients). This proportion is similar to the data reported in the present study (i.
Observed Sea Level Rise During the Twentieth Century Our knowledge of past century sea level change comes from tide gauge measurements located along continental coastlines and islands. The largest tide gauge database of monthly and annual mean sea level records is the Permanent Service for Mean Sea Level (PSMSL, www. pol. ac. uk/psmsl/)  [Woodworth and Player, 2003] , which contains data for the twentieth century from ∼2000 sites. However, only ∼10% of this data set is useable for historical sea level studies because of data gaps and limited tide gauge distribution in the past. Tide gauges measure sea level relatively to the ground, hence monitor ground motions also. In active tectonic and volcanic regions, or in areas subject to strong ground subsidence due to natural causes (e. g. , sediment loading in river deltas) or human activities (groundwater and oil/gas extraction), tide gauge data are directly affected by corresponding ground motions.
Can We Explain Present-Day Global Mean Sea Level Rise? The main factors causing current global mean sea level rise are thermal expansion of sea waters, land ice loss, and fresh water mass exchange between oceans and land water reservoirs (see Figure  2 ). These contributions vary in response to natural climate variability and global climate change induced by anthropogenic GHG emissions. Ocean warming. Analyses of in situ ocean temperature data collected over the past ∼50 years by Expandable Bathy Thermographers (XBT) from ships [e. g. ,  Levitus et al. , 2005 Levitus et al. , , 2009;; Ishii and Kimoto, 2009]  and about the last 10 years by automatic profiling floats from the Argo system  [Roemmich et al. , 2012]  have shown that ocean heat content, and hence ocean thermal expansion, has significantly increased, in particular since 1970, although not linearly [e.
, 2013; Velicogna and Wahr, 2013]. Understanding and reducing these sources of errors (on altimetry-based sea level time series and components) is currently an active research area. Several international projects are or have been recently conducted on that topic, e. g. , the ESA Climate Change Initiative "Sea Level," "Glaciers" and "Ice Sheet" projects, the "Ice2sea" project of the 7th European framework programme, and the "Ice Sheet Mass Balance Exercise"-IMBIE-supported by ESA and NASA. Similar initiatives, e. g. , on Argo data processing should also be implemented shortly. Thus, important progress is expected in the near future in global sea level research. Studies of the historical sea level budget (twentieth century or since 1960) using a combination of observations and model data have also been attempted  [Church et al.
A few studies exist nevertheless from country to continental scale [e. g. ,  Quelennec et al. , 1998; Thieler and Hammar-Klose, 1999]  (Eurosion, www. eurosion. org). They provide quantitative information on shoreline changes and geomorphology gathered in coastal databases through geographical information systems. As an example, the content and coverage of the European coastal database "Eurosion" is provided in Figure  4. Existing coastal databases highlight the heterogeneity of coastline behaviors depending on their geomorphological settings. For example, the European database shows that about 30% of European beaches are currently eroding, whereas 60% of wetlands are accreting. In addition, status of European coastlines significantly differs from the global case: Excluding Scandinavia coasts currently uplifting in response to GIA, only 40% of beaches are found in erosion, which is significantly less than the 70% found at global scale by  Bird [1987].
Acknowledgments We thank  Benoit Meyssignac  and  David Salas-Y-Melia  for providing sea level reconstructions and projections. We also thank  Olivier Henry  for his help in providing some figures. Figures 3 and4 were colorized by  Chromatiques Editions. This work was supported by the  TOSCA program  of the  Centre National d'Etudes Spatiales (CNES) , the  French Geological Survey (BRGM) , and the  ESA Climate Change Initiative  " Sea Level " project.
Process analysis The processes were evaluated using qualitative methods based on primary data collected by the authors (individual interviews, informal interviews, and participant observations) and secondary data from two student theses. The primary data collected by the authors consisted of individual interviews (n = 26). In the Kilwin neighbourhood, in-depth individual interviews were carried out with indigent persons (three on the final list, and three not retained) and with all delegates to the local selection committees (n = 11). In the Polesgo neighbourhood, in-depth individual interviews were carried out with indigent persons (three on the final list, and three not retained) and all the delegates of the local selection committees (n = 3). As mentioned, the Kilwin neighbourhood is four times greater in size than the Polesgo neighbourhood, which explains the smaller number of selection committees in Polesgo and the differences in numbers of stakeholders contacted for the evaluation.
Then, throughout this process in which the authors were involved in discussions, we conducted informal interviews with all the stakeholders (health workers, district managers, all the selected indigents). Participant observations of all interactions over the 15 months of the process provided further data used in this evaluation. The interviews were most often conducted in French, and some in Moré, the predominant language in Ouagadougou. Interviews were audio-recorded, transcribed, and translated into French. For the 12 indigents, only the recordings were used. All interviews were focused on obtaining people's views regarding the intervention's implementation, its problems, its strengths, the adaptation strategies used by the various actors, etc. Subsequently, we performed a thematic content analysis to identify the key aspects of the intervention's implementation.
The data were drawn from the socioeconomic survey of all households carried out by the Ouaga HDSS in 2011 covering the entire population of that area. We used a poverty indicator based on household goods. Households were considered "poor" when they did not have a motorbike, an automobile, a television, or a refrigerator; the methodological details are presented elsewhere  [32, 42]. Inter-group comparisons of means and ratios were done using t-tests. We should point out that we did not analyze the effectiveness of targeting with respect to the indigents identified by the local selection committees and then not retained by the COGES (n = 1,054). Pairing the data for each indigent entered in the local committees' notebooks with the data in the Ouaga HDSS database would have required visiting each of the homes involved, a relatively long process which would have exceeded the budget for this evaluation.
Differences in effectiveness between neighbourhoods Of the 88 indigents selected by both the local committees and the COGESs, 65 (78. 3%) were included in the analysis of effectiveness. This attrition in numbers was related to the mobility of this unstable urban population, and in one case, to death. Individuals (and households) are only entered into the Ouaga HDSS database, by definition, after six months of residence, whereas not all indigents stay put for six months; indeed, some selected indigents left the sector before receiving their card. Moreover, information on household goods was only available for households that the Ouaga HDSS was able to survey when it passed through in 2011 (91. 3% of households), which also reduced the number of indigents included in the effectiveness analysis.
Acknowledgements The community-based process in the two neighbourhoods was organized through a participatory process that involved many people, too numerous to cite here, but to whom we extend our warmest appreciation. O. Ouedraogo  supported the team in implementing the targeting. We also wish to thank the health workers in the two CSPSs and the district health authorities for their availability. This research was funded by a  Canadian Institutes of Health Research (CIHR)  catalyst grant. Valéry Ridde  is the recipient of a CIHR new investigator salary award. The Ouaga HDSS is funded by  Wellcome Trust  (grant number  WT081993MA ). We wish to thank  Patrick Gogognon  and  Matthew R. Hunt  for their reading of a previous version of the article. Finally, the authors would like to thank  Donna Riley  for translation and editing support.