dataesr/scientific-paragraphs-categorization huggingface dataset:
Identifying novel targets There is a clear need for the identification and development of new classes of anti-malarials, i. e. belonging to novel chemical series and with novel modes of action. The current reality is that much drug discovery is still focused on a limited number of historic targets (primarily the folate and haemoglobin degradation pathways), and primarily on the blood stage of the parasite's life cycle. There is a wealth of untapped targets in the various developmental stage proteomes that might be targeted. Databases on genes and metabolic pathways offer opportunities to identify possible new target-based approaches. The cross-correlation of this information can be a very valuable filter (e g, identifying genes that are active in both gametocytes and in the blood stages). Orthology-based screening between Plasmodium species may also give valuable insights into promising new targets.
Finding novel drug classes One approach is the mining of genomic databases to identify novel targets (see below), followed by the screening of high diversity chemical libraries on such targets. Another strategy consists of first using such libraries (including libraries of natural products) in phenotypic screens to constitute the so-called "malaria boxes", and subsequently identify in secondary screens the molecular targets of compounds with parasiticidal activity. Several million chemical entities have been screened for anti-malarial activity, based on whole cell screens of P. falciparum. The screens have included fully synthetic (from both commercially available and pharmaceutical industry proprietary sources) and natural product libraries. More than 20,000 compounds are now available that are known to have selective parasiticidal activity, but whose molecular targets are unknown  [50].
Acknowledgements The Consortium would like to acknowledge the support of the  European Union   FP7  grant that has made the project possible. The Consortium would like to acknowledge the valuable input of the participants in the two workshops that developed the recommendations in this paper: Geneva, Switzerland (May 2010): Stage-specific screening methods  Ian Boulton  ( TropMed Pharma Consulting, UK ),  Foluke Fakorede  ( TDR, Switzerland ),  Jose Garcia-Bustos  ( GlaxoSmithKline, Spain ),  Annette Habluetzel  ( Università di Camerino, Italy ),  Marcel Kaiser  ( Swiss Tropical and Public Health Institute, Switzerland ),  Sumalee Kamchonwongpaisan  ( National Centre for Genetic Engineering & Biotechnology, Thailand ),  Clemens Kocken  ( Biomedical Primate Research Centre, Netherlands ),  Didier Leroy  ( Medicines for Malaria Venture, Switzerland ),  Louis Maes  ( University of Antwerp, Belgium ),  Maria Manuel Mota  ( Universidade de Lisboa, Portugal ),  Maurizio Muraca  ( Ospedale Pediatrico Bambino Gesù, Italy ),  Solomon Nwaka  ( TDR, Switzerland ),  Bernadette Ramirez  ( TDR, Switzerland ),  Tracy Seddon  ( Liverpool School of Tropical Medicine, UK ),  Robert Sinden  ( Imperial College, UK ),  Georges Snounou  ( University Pierre et Marie Curie/INSERM, France ),  Roberta Spaccapelo  ( Università di Perugia, Italy ),  Donatella Taramelli  ( Università di Milano, Italy ),  Chairat Uthaipibull  ( National Centre for Genetic Engineering & Biotechnology, Thailand ),  Henri Vial  ( Centre National de la Recherché Scientifique, University of Montpellier, France ),  Sergio Wittlin  ( Swiss Tropical and Public Health Institute, Switzerland ).
We examine the relation between the galaxy cluster mass M and Sunyaev-Zeldovich (SZ) effect signal D 2 A Y 500 for a sample of 19 objects for which weak lensing (WL) mass measurements obtained from Subaru Telescope data are available in the literature. Hydrostatic X-ray masses are derived from XMM-Newton archive data, and the SZ effect signal is measured from Planck all-sky survey data. We find an M WL -D 2 A Y 500 relation that is consistent in slope and normalisation with previous determinations using weak lensing masses; however, there is a normalisation offset with respect to previous measures based on hydrostatic X-ray mass-proxy relations. We verify that our SZ effect measurements are in excellent agreement with previous determinations from Planck data. For the present sample, the hydrostatic X-ray masses at R 500 are on average ∼ 20 per cent larger than the corresponding weak lensing masses, which is contrary to expectations.
In the latter case, a much larger scatter than expected was found, which the authors attributed to line of sight projection effects in weak lensing mass estimates. In the present paper we make use of the same weak lensing data set from LoCuSS, high quality XMM-Newton archival Xray data, and SZ observations from the Planck 2  All-Sky Survey to investigate the interplay between the different mass measures and the spherically integrated Compton parameter Y SZ in 19 clusters of galaxies. We find that for this particular sample, the weak lensing mass-Y SZ relation at large radii has a slightly higher normalisation than that expected from studies based on hydrostatic X-ray mass estimates. We show that this is due to the hydrostatic X-ray masses being, on average, larger than the corresponding weak lensing masses, in contradiction with the expectations from numerical simulations.
Sample selection and data sets The present investigation requires three fundamental data sets. The first is a homogeneously analysed weak lensing data set with published NFW mass model parameters to enable calculation of the mass at the radius corresponding to any desired density contrast. The second is a good quality X-ray observation data set that allows detection of the X-ray emission to large radius (i. e. , at least up to R 500 ). The third is a good quality SZ data set including high signal-to-noise SZ flux measurements for all systems. While there are many weak lensing investigations of individual objects in the literature, lensing observations of moderately large cluster samples are comparatively rare. For the present comparison, we chose to use published results from LoCuSS, which is an all-sky X-ray-selected sample of 100 massive galaxy clusters at 0.
1 < z < 0. 3 drawn from the REFLEX  (Böhringer et al. 2004 ) and eBCS  (Ebeling et al. 2000)  catalogues, for which gravitational lensing data from the Hubble Space Telescope and Subaru Telescope are being accumulated. At the time of writing, relevant data from only part of the full sample have been published, as detailed below. Results from a Subaru weak lensing analysis of 30 LoCuSS clusters have been published by  Okabe et al. (2010) , who provide NFW mass model parameters for 26 systems. A similar lensing analysis has been undertaken on a further seven merging systems by  Okabe & Umetsu (2008). Excluding the two of these merging clusters that are bimodal and thus not resolved in the Planck beam, we have a total of 31 objects for which the best-fitting NFW profile mass model is available in the literature.
2011 ). Planck's sensitivity, angular resolution, and frequency coverage make it a powerful instrument for Galactic and extragalactic astrophysics as well as cosmology. Early astrophysics results, based on data taken between 13 August 2009 and 7 June 2010, are given in Planck Collaboration VIII-XXVI 2011. Intermediate astrophysics results are now being presented in a series of papers based on data taken between 13 August 2009 and 27 November 2010. All of the 19 systems considered in this paper have been observed by Planck as part of this survey, and indeed their characteristics are such that they are almost all strongly detected, having a median signal-to-noise ratio of ∼ 7.
However, a potentially significant bias may arise from effectively excluding gravitational lensing measurements of galaxies that are smaller than the point spread functions (PSFs) of the Subaru images without imposing a similar size cut on the COSMOS galaxy catalogue. This would also tend to lower the lensing mass estimate by removing the apparently smallest (and thus on average more distant) galaxies, resulting in an overestimate of the mean effective background galaxy redshift compared to the true value. Thirdly, the weak lensing distortion measurements of  Okabe & Umetsu (2008)  and  Okabe et al. (2010)  are based on an implementation of the KSB+ method  (Kaiser et al. 1995; Luppino & Kaiser 1997; Hoekstra et al. 1998). Tests against simulated lensing data  (Heymans et al. 2006; Massey et al.
Here, numerical simulations can also be used to inform the different analyses and to optimise the mass estimation procedure in each case. One possible approach would be to use the centroid of the projected X-ray pressure profile as the point around which both X-ray and weak lensing profiles could be centred. Eventually, X-ray and weak lensing mass estimates will be needed for a representative (or complete) sample of systems. We stress that data quality across such a sample must be as close to homogeneous as possible. In the case of the X-ray data set, the data must be sufficiently deep to measure the temperature profile to R 500. Similarly stringent data quality will also be required for the weak lensing data set.
Acknowledgements. We thank  N. Okabe  and  D. Marrone  for useful discussions. The present work is partly based on observations obtained with  XMM-Newton , an  ESA  science mission with instruments and contributions directly funded by  ESA Member States  and the  USA (NASA). The development of Planck has been supported by:  ESA ;  CNES  and  CNRS/INSU-IN2P3-INP (France) ;  ASI ,  CNR , and  INAF (Italy) ;  NASA and DoE (USA) ;  STFC  and  UKSA (UK) ;  CSIC ,  MICINN  and  JA (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) ; and  DEISA (EU). A description of the Planck Collaboration and a list of its members, including the technical or scientific activities in which they have been involved, can be found at http://www.
Importantly, it is only because Britton et al. make strong simplifying assumptions in their model, such as the independence between network weights and nodes' degrees, that they can derive an explicit form of R 0. In contrast to our findings on NATSAL data, the Reed-Frost approach systematically predicts negative exponential growth rates of the epidemics for both scenarios (the network average of linear case is SR RF 0 T~0:2 and that of survey data case is SR RF 0 T~0:1). The discrepancy between our model and that of  [20]  stems from the implicit assumption of the Reed-Frost model with discrete time steps they use, which is that recovery occurs immediately after infection and therefore that c&b. We extend earlier results by developing a framework based on partial differential equations that allows to model continuous time SIR epidemic dynamics for general weighted networks defined through the joint probability distribution for an individual to have k contacts and l interaction events.
4 ese orienting concepts formed the structural basis for the editorial organisation of all the other products connected to the "Expedição" such as: a book, an exhibition at the Olido Cultural Centre (seat of the Municipal Secretariat of Culture), a video documentary, and the creation of a database in multimedia format that consolidated all the documentation related to contemporary items collected during the journey, in view of the effective creation of the City Museum of São Paulo in 2004. After a change of government in 2005, the project for the new City Museum was discontinued, with only a group of some small historic houses remaining in the scenario; they met neither the contemporary demands of a city museum, nor the scale of a megalopolis like São Paulo. Some of the questions related to the setting up and running of the City Museum are still awaiting answers.
Acknowledgments We thank  Martin Gaitan  for his help to TB during the synthesis of most of the reported compounds. Financial support from  UBACyT  (X219 and  X057 ) and  ANPCyT  ( PICT25409 ) is acknowledged. TB thanks  UNGS  for a research fellowship, FC thanks  CONICET  for a PhD research fellowship. FDC and AZ are members of the research staff of Conicet. BD, BH, and DG thank  CNRS  and  Université de Strasbourg  for their support.
This gives a more narrow degree distribution than the transform proposed in this paper. However, Valentini et al. also conclude that fracture networks are small-world networks  (Valentini et al. , 2007a). In three dimensions where the fractures are sheets, the transformation we propose is necessary to define the topology network. Our analysis is somewhat related to the information measure for cities introduced by  Rosvall et al. (2005). We analyze in the following fracture data from eight outcrops found in south-east Sweden. A detailed description of the bedrock composition and geological history are given in  (Darcel et al. , 2006; Åström, 2007; Ström et al. , 2008). We show one of the outcrop fracture networks in Figure  1A. As we shall see, the equivalent network (shown in Figure  1B ) constructed from the original network has small-world character.
RESULTS Arguably the most central property of any complex network is the degree distribution P(k). The degree, k, of a node is the number of other nodes that it is linked to. The equivalent networks generated from the outcrop networks show a broad degree distribution. We plot the cumulative distribution, P(> k) in Figure  4. When P(k) follows a power-law the network is scale free  (Albert and Barabási, 2002). We plot the data on a log-log scale and fit the average to the power law P(k) ∼ k -2. 2. The scaling ensues over one decade. We note, however, as shown in the insert, that with such a short range, an exponential fit would also match. In the case of the DFN data the goodness of the power law fit is dependent on model parameters. The clustering is a local measure of how well a network is connected on a local neighbor-to-neighbor scale.
, 2010). The angular distribution of the directions of the fractures depends on stress history of the fracture system. We assume here the simplest, i. e. , a uniform distribution. (Åström, 2007)  has measured the angle distribution for some of the data sets we consider here. They are not uniformly distributed. However, there are clear correlations between fracture length and direction in the data sets. This is not captured by a single angle distribution function. Introducing a non-uniform angle distribution in the DFN model does not have a significant impact. Lastly, the position of the fractures must be specified. The DFN model uses a hierarchical construction  (Schertzer and Lovejoy, 1987; Meakin, 1991)  to place the midpoints of the fractures on a fractal set characterized by a fractal dimension D 2.
By tuning the probabilitites P i , the desired fractal dimension D 2 is set, see  (Davy et al. , 2010)  for details. The results of analyzing the equivalent networks of the DFN model networks are given in Table  2. The data are based on 1000 networks of comparable size to those in the outcrop fracture data sets. From the table, we see the same trends as those observed in Table  1  for the eight Outcrop fracture data sets and it is possible to find a combination of α l and D 2 to make match between them. However, we show in Figure  6  the averaged degree correlation matrix. This indicates an assortative network structure: nodes of equal coordination number tend to be connected. This is the opposite of what is observed for the outcrop data sets, see Figure  5. Hence, the topology of the artificial networks is quite different from the natural ones.
This implies that the topology 1 A kink in the slope around k = 60 gives 0. 9 when fitting for smaller values of k and 1. 3 for larger values. of the fracture network themselves, artificial and real, are quite different. This difference is not visible from direct observation. In the study by  Åström (2007) , the outcrop data set is compared with models based on the physical process behind the network. The analysis is performed not on the dual network, but on the fracture network directly. Åström concludes that there are significant discrepancies between the models and the data. These discrepancies are geometrical rather than topological in contrast to the present analysis. Hence, by constructing the equivalent networks, we have access to the entire analysis toolbox of modern network theory for fracture networks.
ACKNOWLEDGMENT We thank  Svensk Kärnbränslehantering AB  for outcrop data and  H. F. Hansen  and  E. Skjetne  for discussions. Christian André Andresen  and  Alex Hansen thank Statoil and The Norwegian Academy of Science and Letters  for funding through their  VISTA program. Sigmund Mongstad Hope  and  Alex Hansen  thank the  Norwegian Research Council  for funding through the  CLIMIT program , grant no. 199970. We also thank the referees for having improved our paper considerably.
e-ISSN 2220-8372 Editor-in-Chief: Dermot Maher, MD, Switzerland Contact: pha@theunion. org PHA website: http://www. theunion. org/index. php/en/journals/pha Article submission: http://mc. manuscriptcentral. com/pha Persons diagnosed with DM are assessed at baseline and annually for additional risk factors for NCDs, late-stage complications and comorbidities such as hypertension, and these along with other patient data are recorded in the e-Health system (see below). Patients are categorised into three main groups: DM type 1, DM type 2 and DM and hypertension, and further classified as new or previously diagnosed. Patients are managed according to a standard algorithm with diet and lifestyle advice, oral hypoglycaemic drugs (glibenclamide, gliclizide and metformin) and insulin, and are assessed as having controlled or uncontrolled DM, based on monthly or quarterly measurements of 2-h postprandial blood glucose (PPBG).
Sources of data, variables, cohort reporting formats and analysis Patient data were obtained from the clinic e-Health systems. Variables included age, sex, category of DM, new or previously known diagnosis of DM, smoking status, physical activity, BMI, and, as of 30 June 2013, treatment outcome, measures of disease control and presence or absence of late-stage complications recorded in Q2 2013. The definitions of variables are shown in Table  1. For the study, the cohorts included new patients registered between 1 April and 30 June 2013 (the quarterly cohort) and all patients ever registered up to 30 June 2013 (the cumulative cohort), with treatment outcomes of the cumulative cohort censored in Q2 up to 30 June 2013. Risk factors, treatment outcomes and late-stage complications were compared between males and females using the χ 2 test, with odds ratios and 95% confidence intervals.
Whole rock geochemistry Sixty samples of typical rock types from the Gruf complex were analysed for major and trace elements: biotite-orthogneisses (18 migmatitic biotite-orthogneisses and 6 enclaverich biotite-orthogneisses), leucogranites (23 samples), charnockites (3 garnet-sillimanite-absent samples, 6 garnetbearing, sillimanite-absent samples and 2 garnet-sillimanitebearing samples) and augengneisses (2 samples). Bulk rock data were obtained using a Panalytical Axios wavelength dispersive XRF spectrometer (WDXRF, 2. 4 kV) at ETH Zurich. Representative bulk rock compositions are given in Table  1. The complete geochemical data are presented in Online Resource 1. Geochemically, the metagranitoids can be divided into two compositional groups. One comprises the migmatitic biotite-orthogneiss, the enclave-rich biotite-orthogneiss, the garnet-sillimanite-free charnockites and the augengneisses.
31 0. 31 0. 41 0. 44 0. 31 0. 26 0. 27 0. 35 0. 33 The complete geochemical database is presented in Online Resource 1 * Total iron as FeO. H 2 O content estimated from Loss of Ignition (LOI); A/CNK = Al 2 O 3 /(CaO ? Na 2 O ? K 2 O)(molar ratio); X Mg = MgO/ (MgO ? FeO).
The 21 st century promises some dramatic changessome expected, others surprising. One of the more surprising changes is the dramatic peaking in car use and an associated increase in the world's urban rail systems. This paper sets out what is happening with the growth of rail, especially in the traditional car dependent cities of the US and Australia, and why this is happening, particularly its relationship to car use declines. It provides new data on the plateau in the speed of urban car transportation that supports rail's increasing role compared to cars in cities everywhere, as well as other structural, economic and cultural changes that indicate a move away from car dependent urbanism. The paper suggests that the rise of urban rail is a contributing factor in peak car use through the relative reduction in speed of traffic compared to transit, especially rail, as well as the growing value of dense, knowledge-based centers that depend on rail access for their viability and cultural attraction.
It is paralleling the phenomenon of peak car use  [37]. It would therefore appear to be reflecting changes in the structure of cities, individual travel behavior and housing preferences, and the beginning of a shift away from the dominant car-based urban sprawl paradigm of the 20 th century. The paper is thus attempting to understand these two phenomena and see how they are linked through the structure of cities. Table  1  above captures the overall picture for a wide range of cities across the globe, summarized into their regional groupings. These data are standardized and comparable in population terms and are systematically collected from transit authorities on a consistent basis. The data show that in all groups of cities there is a very stark difference between rail and bus, with rail leading the transit revival in each group.
Rail seat kilometers per capita have risen much more compared to buses (in Australian and Canadian cities bus service per capita even declined). Likewise, urban rail and bus usage per capita are dramatically contrasted, with urban rail boardings and passenger kilometers showing rather large increases in each group compared to buses and in Singapore/Hong Kong bus boardings even declined. The above data should be seen with the data on car use that were summarized in  [37]  and showed an overall growth of just 5% in the world's cities over the decade from 1995 to 2005, after previous growth of 23%, 26% and 42% in the 80's, 70's and 60's, respectively. The observed dramatic peak in car use and subsequent declines are consistent with the above trends over many decades. Before describing the probable causes of these parallel rail and car trends, various other rail trends will be examined across an even wider array of cities, first in dense European, Asian and Middle Eastern cities, then in low density American and Australian cities.
Emerging Rail Trends in Dense Cities of Europe, Asia and the Middle East This section presents a wide range of data, which collectively demonstrate that urban rail is experiencing a surge of popularity that is perhaps unparalleled since its golden age in the 19 th and first half of the 20 th century. The form of the data presented in this section varies. Although some data are raw and unadjusted for the effects of population growth, system expansion and increases in rail service levels, and therefore can be criticized for this, such increases in the availability of rail systems are themselves part of the current ascendency of rail in cities and therefore integral to the argument in the paper. In short, rail systems are being expanded, they are increasing their service levels and they are being better utilized, which is the essence of the paper.