dataesr/scientific-paragraphs-categorization huggingface dataset:
The current Biogrid Index  [45, 46]  version 3. 3. 124 (http://thebiogrid. org/), holds more than 820,000 protein interactions derived from highthroughput datasets, individual focused experiments, and from over 44,000 publications. The types of proteinprotein interactions include actual chemical bonding, or temporary bonds known as secondary bonding, and the concentration of the specific proteins dictates the degree of interaction. If a protein is in limited supply, it is said to have low chemical potential, and if it is abundant, it is said to have high chemical potential. Thus, using protein concentration, we can calculate the chemical potential of each protein in the network (i. e. Gibbs free energy), compute a topological measure known as filtration threshold (an energy threshold), and "filter out" the most energetic subnetworks from the larger network and try to reduce complexity of these subnetworks by inhibiting each protein in turn.
A POTENTIAL SOLUTION A potential solution to managing the information glut and helping the oncologist to provide patients with the right combination of targeted agents and chemotherapy, is to enable them to use all of the available information. While producing complete genomic, proteomic and metabolomics datasets for each patient is not feasible at present, it has been possible in some well-funded research units to access the entire tumor and host transcriptomic information. The more complete the information provided for the analysis of the involved pathway(s), the more complete the therapeutic coverage. Unfortunately, for most physicians practicing clinical oncology today, the most feasible option is using a panel of candidate genes, because this may be covered by the patient's insurance.
clinicaltrials. org now lists over 150 trials that use the word "metronomic" in their title. The mechanism of action of metronomic chemotherapy has been subject to excellent recent reviews,  [75]  and its value to implementation of precision medicine well documented. [22]  To summarize briefly, because of the side effects induced by maximally dosed chemotherapy, the duration of the therapy has to be limited and breaks for bone marrow recovery incorporated. Furthermore, because conventional chemotherapy targets only proliferating malignant cells, a large portion of malignant cells is not affected. Only once these cells are re-engaged in the cell cycle process cytotoxic drugs are able to corrode them. Metronomic therapy implies that the use of low, continuous doses of chemotherapy in combination with biologic response modifiers not only avoid toxic side effects, but also preferentially target the host biological responses such as stromal induction,  [76]  angiogenesis,  [68, 77, 78]  immune surveillance,  [75, 79, 80]  and inflammation.
A POTENTIAL SOLUTION In the coming decade(s) a background for the combination therapies will be applied for any patients with chemotherapy resistant cancer or for patients with very poor prognosis. As much information as possible should be gathered about the patient's tumor molecular signature, about the host specific germline gene alterations, and about the host phenotype as soon as possible, so as to avoid unnecessary toxicities and delays with standard therapies whenever success cannot be reasonable expectation. The hope is that data from each of these cases will be collected www. impactjournals. com/oncotarget and each of the individual outcomes will inform any future therapeutic decision.
ACKNOWLEDGMENTS The authors are grateful for the many informal discussions with pediatric oncologists attending the October 2015 CEPOETA meeting in Brno, Czech Republic. GLK would like to acknowledge the philanthropic support from the  Campanelli Foundation ,  CSTS Health Care , and institutional support. ER, AH, CK and PC have received salary support from  CSTS Health Care. JS and OS were supported by  Czech Republic Ministry of Health  grant  16-33209A  and  16-34083A. OS was also supported by the  Ministry of Education, Youth and Sports of the Czech Republic  under the project  CEITEC 2020  ( LQ1601 ). DV was supported by  Czech Republic Ministry of Education, Youth and Sports  grant  LM2015089. CK was supported by the grant of the  Hungarian National Scientific Research Fund   OTKA K-108885.
Geographic distribution of authors, who published papers in Chemistry Journal of Moldova. Over the past decade, with the strong support from leading professionals around the world, the Journal has grown and become one of the well-established international publications in the fi eld. In 2015 Chemistry Journal of Moldova was included in Thomson Reuters-Emerging Source Citation Index (ESCI) based on relevance to a scholarly community, interest to opinion leaders, coverage of emerging fi elds, and feedback given by Web of Science customers. I would like to mention that Chemistry Journal of Moldova is indexed by leading International Indexing agencies and databases like: CAS, DOAJ, BASE, HINARI, OAJI, EVISA, VINITI, ROAD etc. Chemistry Journal of Moldova is under evaluation for SCOPUS. Starting from 2016 year, each published paper has been assigned a unique Digital Object Identifi er (DOI).
Introduction The 'sud4science' project (http://sud4science. org;  Panckhurst et al. , 2013)  is part of a vast international initiative, entitled 'sms4science' (http://www. sms4science. org/; Fairon et al. , 2006; Cougnon and Fairon, 2014; Cougnon, 2015) , which aims to build a worldwide database and analyse authentic text messages in different languages-mainly French, but also Creole, Swiss German, Standard German, Italian, Romansh  (Du ¨rscheid and Stark, 2011) , and English  (Guilbault and Drouin, 2016). Several related SMS data collections have taken place since the initial Belgian one: Reunion Island (20,000 SMS, 2008, http://www. lareunion4science. org/; Cougnon and Ledegen, 2010) ,  Switzerland (24,000 SMS, 2009-10, http://www. sms4science. uzh. ch; Du ¨rscheid and Stark, 2011) , Quebec (5,000 SMS, 2010, http:// www.
, 2014 , Patel et al. , 2013). Two extracts were 'transcoded' into standardized French (1,000 SMS) and linguistically annotated (100 SMS). In June 2014, the finalized digital resource of 88,000 anonymized French text messages, the '88milSMS' corpus, the extracts, and the sociolinguistic questionnaire data were made available for all to download, from the Huma-Num web service (http://88milsms. huma-num. fr; Panckhurst et al. , 2014). The 88milSMS corpus has also recently become available via a Creative Commons Attribution 4. 0 International (CC BY 4. 0) licence on the 'Ortolang' platform (https://hdl. handle. net/ 11403/comere/cmr-88milsms/cmr-88milsms-tei-v1;  Panckhurst et al. , in Chanier (ed) 2016). In this article, after briefly evoking the anonymization process, I focus on why we decided to exclude full 'transcoding' and linguistic annotation from the final processing of the first version of the 88milSMS corpus.
Typographical norms are also reinserted; in this example, a space before the question mark in French and a capital 'M' for the city of Montpellier. What if a texter tries to simulate a certain form of oral French, for instance, by using an apostrophe, or through agglutination ('j'sais'¼'je sais', 'chuis'¼'je suis') as shown above? Should these items be transcoded or not? What about punctuation, often absent in text messages? Should one re-introduce this systematically? Example three shows how difficult the transcoding process can be. Researchers may well have differing theoretical viewpoints on these matters. In November 2011, the Montpellier team invited researchers involved in previous sms4science data collections to a twoday workshop to exchange views on harmonization/ standardization techniques related to anonymization, transcoding, and annotation for processing SMS written data.
Annotation Another issue is linguistic annotation of the corpus (Ide and Pustejovsky, forthcoming). For example, the 'raw' SMS 'je met tout ca de coteet peux tout encaisser juste pour toi. ' (I'm leaving all of that aside and I can bear it all just for you. ) could be transcoded into standardized French as follows: 'Je mets tout ca de coteet je peux tout encaisser juste pour toi. ' It could then be linguistically annotated with information of interest to researchers, among other items: spelling, grammatical information, emoji insertion, code-switching, typography, missing accents, voluntary modification, etc. Therefore, I define linguistic annotation of SMS data for the 88milSMS corpus, as 'interpretative' linguistic mation indicated via appropriate tags (see below), related to the difference between a 'raw' text message and its transcoded equivalent in standardized French.
Acknowledgements I would like to thank two anonymous reviewers for their valuable and thought-provoking remarks. Any remaining mistakes are of course my own. This work was supported by the  MSH-M (Maison des Sciences de l'Homme de Montpellier, France , http://www. msh-m. fr/), the DGLFLF (Delegation generale ala langue francaise et aux langues de France, http://www. dglflf. culture. gouv. fr/), and the  CNRS (PEPS ECOMESS, HuMaIn ). The SMS data described in this article was collected within the framework of the sud4science LR (http:// www. sud4science. org)project. It is part of a vast international SMS data collection project, entitled sms4science (http://www. sms4science. org),and was initiated at the  CENTAL (Centre for Natural Language Processing, UniversiteCatholique de Louvain, Belgium ) in 2004.
1. Unlike the SUSY razor searches  [33, 35] , which focus on events with large values of M R , this study also considers events with small values of M R , using R 2 to discriminate between signal and background, in a kinematic region (R 2 > 0. 5) excluded by the baseline selection of Refs. [33, 35]. A data sample corresponding to an integrated luminosity of 18. 8 fb -1 of pp collisions at a center-of-mass energy of 8 TeV was collected by the CMS experiment with a trigger based on a loose selection on M R and R 2. This and other special triggers were operated in 2012 to record events at a rate higher than the CMS computing system could process during data taking. The events from these triggers were stored on tape and their reconstruction was delayed until 2013, to profit from the larger availability of processing resources during the LHC shutdown.
Summary A search for dark matter has been performed studying proton-proton collisions collected with the CMS detector at the LHC at a center-of-mass energy of 8 TeV. The data correspond to an integrated luminosity of 18. 8 fb -1 , collected with a dedicated high-rate trigger in 2012, made possible by the creation of parked data, and processed during the LHC shutdown in 2013. Events with at least two jets are analyzed by studying the distribution in the (M R , R 2 ) plane, in an event topology complementary to that of monojet searches. Events with one or two muons are used in conjunction with simulated samples, to predict the expected background from standard model processes, mainly Z+jets and W+jets. The analysis is performed on events both with and without b-tagged jets, originating from the hadronization of a bottom quark, where in the latter case the dominant background comes from tt.
Acknowledgments We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at  CERN  and at other  CMS institutes  for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centers and personnel of the Worldwide LHC Computing Grid for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies: the  Austrian Federal Ministry of Science, Research and Economy  and the  Austrian Science Fund ; the  Belgian Fonds de la Recherche Scientifique , and  Fonds voor Wetenschappelijk Onderzoek ; the  Brazilian Funding Agencies (CNPq, CAPES ,  FAPERJ , and  FAPESP) ; the  Bulgarian Ministry of Education and Science ; CERN; the  Chinese Academy of Sciences, Ministry of Science and Technology , and  National Natural Science Foundation of China ; the  Colombian Funding Agency (COLCIENCIAS) ; the  Croatian Ministry of Science, Education and Sport , and the  Croatian Science Foundation ; the  Research Promotion Foundation , Cyprus; the  Ministry of Education and Research, Estonian Research Council  via  IUT23-4  and  IUT23-6  and  European Regional Development Fund , Estonia; the  Academy of Finland ,  Finnish Ministry of Education and Culture , and  Helsinki Institute of Physics ; the  Institut National de Physique Nucléaire et de Physique des Particules / CNRS , and  Commissariat à l' Énergie Atomique et aux Énergies Alternatives / CEA , France; the  Bundesministerium f ür Bildung und Forschung, Deutsche Forschungsgemeinschaft , and  Helmholtz-Gemeinschaft Deutscher Forschungszentren, Germany ; the  General Secretariat for Research and Technology, Greece ; the  National Scientific Research Foundation , and  National Innovation Office, Hungary ; the  Department of Atomic Energy  and the  Department of Science and Technology, India ; the  Institute for Studies in Theoretical Physics and Mathematics, Iran ; the  Science Foundation, Ireland ; the  Istituto Nazionale di Fisica Nucleare, Italy ; the  Ministry of Science, ICT and Future Planning , and  National Research Foundation (NRF) ,  Republic of Ko-.
Acknowledgements This work was supported by the  Mairie de Paris (Emergence  (s) 2012). M. A. acknowledges funding from the  European Commission  ( FP7 PEOPLE 2013 IEF/Project 624806  " DIOPTRA "). N. K. thanks  Maria Vladimirova  ( L2C ,  CNRS ) for help with data analysis and  Alexey Kavokin  ( University of Southampton ) for discussion.
Planck observations at 353 GHz provide the first fully-sampled maps of the polarized dust emission towards interstellar filaments and their backgrounds (i. e. , the emission observed in the surroundings of the filaments). The data allow us to determine the intrinsic polarization properties of the filaments and therefore to provide insight on the structure of their magnetic field (B). We present the polarization maps of three nearby (several parsecs long) star forming filaments of moderate column density (N H about 10 22 cm -2 ): Musca, B211, and L1506. These three filaments are detected above the background in dust total and polarized emission. We use the spatial information to separate Stokes I, Q, and U of the filaments from those of their backgrounds, an essential step to measure the intrinsic polarization fraction (p) and angle (ψ) of each emission component.
XIX 2015; Planck Collaboration X 2015). Planck Collaboration Int. XXXII (2014) identify interstellar filaments over the intermediate latitude sky, and present a statistical analysis of their orientation with respect to the component of the magnetic field on the POS (B POS ). In the diffuse ISM, filaments are preferentially aligned with B POS. Towards nearby molecular clouds the relative orientation changes progressively from preferentially parallel to preferentially perpendicular from the lowest to the highest column densities  (Planck Collaboration Int. XXXV 2015). In this paper, we make use of the Planck polarization data to study the structure of the magnetic field within three fields comprising the archetype examples of star forming filaments of moderate column density: B211, L1506, and Musca.
Characterizing the magnetic field structure in such filaments, and its connection with that of the surrounding cloud, is a step towards understanding the role of the magnetic field in their formation and evolution. Stellar polarization data in these fields have been reported by several authors  (Goodman et al. 1990; Pereyra & Magalhães 2004; Chapman et al. 2011). With Planck we have now access to fully-sampled maps of the dust polarized emission of both the filaments and their surrounding environment. The spatial information allow us to derive the polarization properties intrinsic to the filaments after subtracting the contribution of the surrounding background to the Stokes I, Q, and U maps. We relate the results of our data analysis to the structure of the magnetic field. The paper is organized as follows.
The Planck data at 353 GHz and the relations used to derive the polarization parameters from the Stokes I, Q, and U maps are presented in Sect. 2. In Sect. 3, we present the I, Q, and U maps of the three filaments and their profiles perpendicular to their axes. In Sect. 4 we quantify the variations of the polarization angle and fraction from the background to the filaments, and within the filaments. Section 5 discusses possible interpretations of the observed decrease of p from the background to the filaments. Section 6 summarizes the results of our data analysis and presents perspectives to further studies. In Appendix A, we present a two-component model that applies as a first approximation to the polarized emission from interstellar filaments and their backgrounds.
2 ). ence direction; the position angle (PA) of each segment (1 to 7) is estimated from the mean tangential direction to the filament crest. The parameter Q rot is positive and U rot = 0 if the magnetic field is perpendicular to the filament axis. The data (Fig. 3 ) show that most of the polarized emission of segments 1 to 5 is associated with Q rot > 0 and Q rot > |U rot |. This is consistent with a magnetic field close to perpendicular to the filament axis. For the segments 6 and 7, the relative orientation between the B POS angle and the filament is different as indicated by the Q rot and U rot profiles.
A two-component model: filament and background The observed polarized emission results from the integration along the LOS of the Stokes parameters. We take this into account by separating the filament and background emission using the spatial information of the Planck maps. We describe the dust emission observed towards the filaments as a simplified model with two components. One component corresponds to the filament, for |r| < R out , where r is the radial position relative to the filament axis (r = 0) and R out is the outer radius. The other component represents the background. They are the largest for low p and N H values. The mean errorbar on p is 1. 2 % for the data points used for the linear fits, and 2. 5 % for the points where p < 3 % and N H < 3 × 10 21 cm -2. We define as background the emission that is observed in the vicinity of a filament.
9. These mean profiles are obtained by averaging data within the selected fields in the direction parallel to the filament axes. They are related to the profiles presented in Sect. 3 as follows. The mean profile of Musca corresponds to the averaging of profiles 4 and 5 in Fig. 2 , that of the B211 filament to profiles 1 to 4 in Fig. 5 , and for L1506 to the profiles 2 to 4 in Fig. 6. Figure  9  displays the fits of the I, Q and U profiles for |r| > R out with polynomial functions of degree three and interpolated for |r| < R out. The fits reproduce well the variations of the background emission outside of the filaments (Fig. 9 ). Planck collaboration: Signature of the magnetic field geometry of interstellar filaments in dust polarization maps.
XIX 2015). In such a model, we expect the dispersion of ψ to be close to σ max ψ in the background and much smaller in the filament (see Fig. 9  in  Jones et al. 1992 ). This prediction is inconsistent with our data because (1) σ ψ bg is much smaller than σ max ψ , and (2) it is comparable to and even smaller than σ ψ fil (Table  2 ). Moreover Fig. 11  shows that the variations of the magnetic field orientation are not random. Systematic variations of the polarization angle along and across the filaments must also exist on scales unresolved by Planck observations. Hence, we expect some depolarization from coherent changes of the field orientation in the beam and along the LOS. Spectroscopic observations of B211 show density and velocity structures on scales five times smaller than the Planck beam, and coherent over lengths of ∼ 0.
Acknowledgements. The Planck Collaboration acknowledges the support of:  ESA ;  CNES , and  CNRS/INSU-IN2P3-INP (France) ;  ASI ,  CNR , and  INAF (Italy) ;  NASA and DoE (USA) ;  STFC  and  UKSA (UK) ;  CSIC ,  MINECO ,  JA  and  RES (Spain) ;  Tekes, AoF , and  CSC (Finland) ;  DLR  and  MPG (Germany) ;  CSA (Canada) ;  DTU Space (Denmark) ;  SER/SSO (Switzerland) ;  RCN (Norway) ;  SFI (Ireland) ;  FCT/MCTES (Portugal) ;  ERC  and  PRACE (EU). A description of the Planck Collaboration and a list of its members, indicating which technical or scientific activities they have been involved in, can be found at http://www. cosmos. esa. int/web/planck/planck-collaboration. The research leading to these results has received funding from the  European Research Council  under the European Union's  Seventh Framework Programme  ( FP7/2007-2013)  /  ERC  grant agreement No.
Background In September, 2015, the UN General Assembly established the Sustainable Development Goals (SDGs). The SDGs specify 17 universal goals, 169 targets, and 230 indicators leading up to 2030. We provide an analysis of 33 health-related SDG indicators based on the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015). Methods We applied statistical methods to systematically compiled data to estimate the performance of 33 healthrelated SDG indicators for 188 countries from 1990 to 2015. We rescaled each indicator on a scale from 0 (worst observed value between 1990 and 2015) to 100 (best observed). Indices representing all 33 health-related SDG indicators (health-related SDG index), health-related SDG indicators included in the Millennium Development Goals (MDG index), and health-related indicators not included in the MDGs (non-MDG index) were computed as the geometric mean of the rescaled indicators by SDG target.
Of the 47 health-related indicators included as part of the SDGs, estimates for 33 indicators are presently included as part of GBD. The GBD study also has several mechanisms to ensure independence, including the GBD Scientifi c Council that meets regularly to review all methods and major data changes, and the Independent Advisory Committee that meets twice yearly to review GBD progress and provide recommendations for strengthening GBD estimates. 33 n this analysis, while acknowledging the continued debate about the structure, selection, and construction of SDG indicators, we used the GBD study to assess the current status of these 33 health-related SDG indicators. With this baseline assessment, we developed and estimated a summary indicator for the health-related SDG indicators and documented historical trends for this summary indicator.
Overview of GBD GBD is an annual eff ort to measure the health of populations at regional, country, and selected subnational levels. 33 GBD produces estimates of mortality and morbidity by cause, age, sex, and country for the period 1990 to the most recent year, refl ecting all available data sources adjusted for bias. GBD also measures many health system characteristics, risk factor exposure, and mortality and morbidity attributable to these risks. In addition to providing highly detailed standardised information for many outcomes and risks, various summary measures are also computed, including disability-adjusted life-years (DALYs) and healthy life expectancy. For the present analysis, we used estimates from GBD 2015 to provide a baseline assessment for 188 countries. [36] [37] [38] [39].