dataesr/scientific-paragraphs-categorization huggingface dataset:
Conclusion In this work, we have investigated the capabilities of information-theoretic random field models to accurately represent mesoscopic elasticity fields obtained through the filtering procedure proposed in  (Bignonnet et al. , 2014). Tab. 1. Comparison between the effectives moduli derived from the experimental database and the probabilistic model (the 99% confidence interval is reported). For illustration purposes, the analysis has been performed on a simple but non-trivial model microstructure. We first introduced a random field model and addressed the calibration task by using either statistical estimators or the maximum likelihood principle. A comparison on some quantities of interest, such as the effective properties, was subsequently carried out. It is shown that for the case under study, the information-theoretic model can be calibrated on a limited set of realizations and still allows for accurate predictions of the effective properties, hence allowing for substantial computational savings in numerical homogenization.
We also collected results of blood samples for VL and CD4 T-cells (count and percentage), at least every two months for the next six months after intensification, and at 12 months. Plasma VL was evaluated by Roche Cobas Taq man HIV-1 v. 2. 0 test with a detection limit of 20 copies/ml. Coreceptor usage was determined from RNA genotypic analysis of the V3 env. region sequence by Geno2Pheno2 algorithm. Quantitative data are presented as median [IQR] values, unless otherwise stated in text. Wilcoxon signed-rank test was used to test the paired differences in values obtained from baseline to each step of study for significance. A Chi-2 test adapted for small numbers was used to test the difference in rates of VL under threshold between the different groups.
56)), rabbit anti-b-tubulin antibody (1:50,000, Abcam ab6046), HRP conjugated secondary antibodies (1:3,000, Bio-Rad) and IRDye infrared fluorescent dyes (1:10,000, LI-COR). Inhibitors and treatments were used at the following concentrations: Pifithrin-a (Sigma) 10 mM, p38 inhibitor SB202190 (Calbiochem) 10 mM, ROCK inhibitor Y27632 (Sigma) 30 mM, Piezo inhibitor gadolinium III chloride (Sigma) 100 mM, S1P2 inhibitor JTE013 (Tocris Bioscience) 10 mM, tetracycline (Sigma) 5 mg ml À 1 (except for pre-treating scrib KD cells for RNA-seq analysis where it was used at 10 mg ml À 1 ), doxycycline (Sigma) 1 mg ml À 1 , Nutlin-3 (Cayman Chemicals) was added as specified. Cell culture and plasmids. The cell lines used in this publication are not listed in the database of misidentified cell lines maintained by ICLAC.
In control cultures, wild-type (unlabelled) cells were plated with wild-type Rosa26R-Tomato (nuclear red) cells (MTEC Tomato)  48  cells at a 2:1 ratio. In competition cultures, unlabelled p53-null cells (MTEC p53 À / À ) and wild-type Rosa26R-Tomato cells (MTEC Tomato) were plated at a 2:1 ratio. Nutlin-3 was added at 17. 5 mM on day 3 of live imaging. The medium was changed every 2 days. Homeostatic cell density assays. These assays were carried out in 96-well plates. GFP-labelled scrib KD and scrib KD p53 À / À cells (8,000-12,000 cells per plate) were pre-treated with tetracycline for 12 h before plating where applicable, in the presence or absence of inhibitors. Where applicable, Nutlin-3 was added 24 h after plating. The whole well was then imaged and the individual images were stitched together for further analysis to obtain data on total cell number and density.
Quantifications for LI-COR blots were carried out using Image studio lite (http://www. licor. com/bio/products/software/image_studio_lite/ ?gclid=COWG_Yze98MCFYvpwgodfR8Adg), using Actin to normalize the samples for loading. For original full blots, see Supplementary Fig. 9. RNA-seq and differential expression analysis. RNA-seq libraries were prepared with the TrueSeq RNA sample preparation V2 kit (Illumina) according to the manufacturer's instructions, and sequenced on an Illumina HiSeq 2000 instrument in single-read mode at 36 or 40 base length. The resulting fastq files were filtered for low-quality reads (oQ20) and low-quality bases were trimmed from the ends of the reads (oQ20). Genome-based RNA-seq mapping was carried out using Canis lupus familiaris 3. 1 (NCBI/Dog Sequencing Consortium) as a reference genome.
Transcript sequences were assigned to genome using BLAT  62. The resulting mappings were filtered by a mismatch threshold (2%), as well as requiring 90% of the transcript to match the genome and all exons to match a single chromosome. This resulted in 21,571 transcripts mapping to the genome. This mapping was used as a junction file for Tophat 2 (ref. 63), which was used to map the RNA-seq reads to the genome. To provide gene names, transcript sequences were downloaded from the NCBI RefSeq database in March 2013 (24,538 sequences). Orthologues were found against the Mus musculus proteome (downloaded in January 2013-NCBI RefSeq) using Inparanoid  64. The sequences were further annotated using InterProScan  65  to provide both InterPro Domains and Panther ontology terms  66. For differential expression, read counts were generated by quantifying overlaps with transcript locations.
These were then used to generate RPKMs. Comparisons were made between pairs of conditions, each with at least four replicates. For a transcript to be included, counts per million had to be above 10 for all samples in at least one condition and within 2-fold between replicates. Differentially expressed transcripts were then called using EdgeR 67. Hits were selected applying the following thresholds: P40. 05 log FC (fold change) 40. 5. Gene Ontology terms overrepresented among these lists were found using David Bioinformatics Resources  68  , in particular, KEGG pathway analysis. Experiments in Drosophila wing discs. Flies were raised on a standard fly food containing yeast at 25 °C. The larvae were collected at wandering third instar stage. Clones in wing discs were induced either with en-FLP (Supplementary Fig.
Acknowledgements This work was supported by a  Cancer Research UK Programme  Grant (E. P. and L. W. A12460), a  Royal Society University Research fellowship  to E. P. ( UF0905080 ), a  Wellcome Trust   PhD studentship  to I. K. , a  Cambridge Cancer Centre PhD studentship  to M. G. , a  European Research Council (ERC)  grant  to R. E. C. S. (243283-SYSGRO ), a  BBSRC grant  ( R. E. C. S. and A. C. BB/K006320/1 ) and Core grant funding from the  Wellcome Trust  ( 092096 ) and  CRUK  ( C6946/A14492 ). The ' Biology-Inspired Physics at Mesoscales ' group is a member of the  IPGG Labex. The laboratoire  PhysicoChimie Curie  is member of the  Labex CelTisPhyBio Labex. We thank:  Yasuyuki Fujita  for providing scrib KD and E-cad KD MDCK cells and an E-cadherin shRNA construct;  Richard Butler ,  Nicola Lawrence  and  Alex Sossick  for help with microscopy and image analysis;  Nicolas Carpi  and  Matthieu Piel  for advice on the use of stretchers;  James Nelson  for E-cadherin constructs and discussions;  Silvia Vivarelli  for cloning pGIPZ-GFP-NLS and pGIPZ-RFP-NLS and researchers cited in methods for reagents.
3  and in Ref. [26]  (Fig. 1 ) for larger particles. ΔP collapse characterizes the resistance of each armored bubble against gas dissolution. Its variation with the physical parameters is determined by repeating the experiment for several armor radii and three different particle sizes. The results are presented in Fig. 3(b) , where ΔP collapse is plotted against 1=R, the inverse of the radius of the spherical armor in the jammed state before buckling occurs. We observe that ΔP collapse decreases when the size of the shell increases. Indeed, a linear fit between ΔP collapse and 1=R shows good agreement with the data up to 1=R ≃ 0. 03 μm -1 (R ≃ 33 μm), as shown by the dashed line in Fig. 3(b). The slope of the fitted line is 104 mN=m, which corresponds to 1. 5γ, where γ ¼ 70 mN=m is the estimated surface tension.
ACKNOWLEDGMENTS The authors thank Caroline Frot for help with the microfabrication. Useful discussions with Arezki Boudaoud and Emmanuel de Langre are gratefully acknowledged. The blue-green curves display the overpressure felt by a bubble as a function of its inverse radius R in a foam with a log-normal bubble-size distribution. The mean of the distribution is kept constant at 100 μm, while the standard deviation is varied from 3. 5 μm (blue) to 84 μm (green), as shown in the lower inset. The black line represents the resistance ΔP Ã of a colloidal shell as defined by our model and our experiments. Bubbles subjected to a pressure below this critical value will collapse and disappear, while the others will remain stable. The case of unarmored bubbles (ΔP ¼ 0) is displayed in gray for comparison.
Microfluidics The experiments were conducted in PDMS (Sylgard 184, Dow Corning) microchannels, plasma bonded to glass. A mold (see Fig. 6 ) was first micromilled in a brass block using a CNC micromilling machine (Minitech), following a 3D model of the channel drawn using CAM software (Rhinoceros). Liquid PDMS was then cast over the mold and cured on a hot plate at 150 °C for at least 24 h. This thermal aging was necessary to reduce the hydrophobic recovery of the PDMS after plasma treatment  [42]. The patterned PDMS was then sealed to a glass slide after 30 s in an air plasma, and the resulting channel was immediately filled with distilled water (Milli-Q) to ensure that the walls remain hydrophilic. The microfluidic chips were stored in a 100% humidity sealed container in order to prevent drying and to keep the channels hydrophilic.
Fluids were flowed into the channels using Teflon (PTFE) tubing and glass syringes driven by syringe pumps (Nemesys, Cetoni). The ambient pressure inside the microsystem was controlled by an external pressure controller (MFCS, Fluigent). The temperature was regulated at 50 °C by placing the microchip on a heated microscope stage (Warner Instruments). The bubbles were monitored by phase contrast or fluorescence microscopy (Eclipse Ti, Nikon) using a CCD camera (Insight, SPOT). We estimated the evolution of the volume of gas inside the bubble by measuring the projected area of the bubble by gray-level threshold image analysis (Matlab).
The European Habitat Directive encompasses a conservation policy devoted to conserve habitats rather than single species. This ambition has strong ecological justifications, and inspires other initiatives such as the IUCN red list of ecosystems. Evaluating this policy is therefore pivotal to identify and reproduce best practices. However, the habitat aspect of this policy has so far not been systematically assessed. To make up for this lacuna, we take advantage of decisionaiding methodologies to introduce a new normative framework. According to this framework, a conservation policy is positively evaluated if it contributes to conservation, is science-based, operational, and legitimate. Based on an exploration of the published literature and unpublished reports and databases, we identify knowledge gaps plaguing the European habitat conservation policy.
We reported the categories used in these articles to describe habitats (column 2) and identified in each case a series of HCI and non-HCI categories (including syntaxons) to which each category could correspond (column 3). This table illustrates that, on the basis of the information given in published articles, it is impossible to translate unequivocally the language used by functional ecologists to describe habitats into the one used by HCI practitioners. To develop our evaluation, we first introduce a new normative framework inspired by recent advances in decision-aiding methodologies. Although the abovementioned assessments exclusively focus on the impact of N2000 on conservation targets, this framework encompasses several dimensions of evaluation. Then, exploring the literature and unpublished reports and databases, we identify knowledge gaps (KG) plaguing HD's habitat policy.
Lack of data on HCI conservation status (KG1) HD requires that Member States periodically perform conservation status assessments of HCI along three ecological parameters: range, coverage, and structure and function (article 17 evaluation: A17E). In each country, each HCI is evaluated in each biogeographical region (SI-   1-C2 ). According to these databases, in France, evaluations based on a "complete survey or a statistically robust estimate" (in the official terminology: SI-Table  1 -A4) are marginal (6. 3%). 52. 5% of evaluations are admitted to be based on data that are "partial" and 38% are "based on expert opinion. " The lack of data is especially patent for structure and function: 85% of evaluations are expert opinions (SI-Table  1-C2 ). This can be compared with evaluations of population size and population trends of Bird SCI in France in the BD reporting (SI-Table 1-C3), among which 44% are complete surveys and 7% are expert opinions.
At European level, complete or statistically robust surveys are more important but in minority (16. 6%), experts opinion are less dominating but still important (22. 7%), and significantly more so (χ ²-test: P < 0. 001) for structure and function (43. 4%). For each biogeographical zone/country/HCI combination, A17E provides an aggregate conservation status for all sites inside and outside N2000. A handful of countries (France, UK, Belgium, Germany, and Austria: SI-Table  1 -A4) also produce evaluations at site level. However, these initiatives lack coordination  (Maciejewski et al. 2016). The site-level French database (SI-Table  1 -C4) contains information encoded in categories different from the ones used in A17E, with admitted ambiguities of translations between the two (SI-Table 1-A5).
Definitions of habitats in practitioner's manuals (SI-Table  1 -A7) are however based on lists of "index species" often including invasive species. Depending on the invasive database used, 8-28% of the HCI present in France have, among their "index species," at least one species considered invasive in France (SI-Table  3 ). Robust knowledge on the impact of invasive species on HCI is therefore greatly needed, especially for HCI with index invasive species. However, to date, only four articles display results on the impact of invasive species on HCI (Figure  2b ). (c) Conservation planning because  Popescu et al. (2014)  identified it as the dominant discipline in the N2000 literature. We identified only 24 articles pertaining to this discipline on habitats (suggesting that the literature identified by  Popescu et al.
Deficiencies in the structure of the epistemic community (KG4) One of the strengths of N2000 is that numerous international experts were involved in its construction through seminars and experts groups  (Evans 2012; Popescu et al. 2014). However, the French A17E database reveals problems in the structure of these panels. Although A17E involved more than 800 contributors, writing was largely confined to expertise institutions (81%), whereas research and teaching institutions played a marginal role (<5%). Among the 319 evaluations by expert institutions, all but one were performed by "Conservatoires Botaniques," institutions representing botanists and phytosociologists. The relevance of these actors for A17E is indisputable but others, including researchers and managers, also have insights to contribute, and the panel is biased against them (Figure  4 ).
Social and economic scientists or experts could also contribute by improving the identification of threats impacting habitats and policies contradicting N2000 actions. Going beyond Figure  4  Institutional and disciplinary balance in the composition of the panel involved in the latest A17E in France. These information are from the French A17E database (SI-Table  1-C2 ). The database provides names and institutional affiliations for most of the experts involved in the evaluation. Part (a) of the graph reproduces the data from this database. To construct part (b), we used the disciplinary affiliation presented by the various experts on the websites of their institutions. "Conservatoires Botaniques" are the only exception, because most of the experts from these institutions do not have a personal page presenting them in the website of the "Conservatoire Botaniques" to which they belong.
Since "Conservatoires Botaniques" are institutions devoted to botany and phytosociology, we classified experts from Conservatoires Botaniques in the disciplinary category "phytosociology. " European guidelines, the French database, therefore, unveils problematic biases invisible at European level. Moreover, as far as reports indicate (SI-Table  1 -A8), it has not been verified that the various A17E evaluators agreed in their understanding of "conservation status". The European guidelines (SI-Table 1-A4) do not require any such verification. Similarly, the construction of site scale methods (SI-Table 1-A9-A19) admits that "conservation status" is unproblematic for the panel of experts involved. Recent discussions  (Epstein et al. (2016)  on species,  Boitani et al. (2015)  on ecosystems,  Maciejewski et al.
Building capacity Strengthening scientific bases is, however, only one aspect of the improvements needed. By adopting HD, Member States committed to equip themselves with the capacity to implement it. In France, reference institutions for habitats are "Conservatoires Botaniques. " Their botanical competence is indisputable but they have neither the obligation nor the financial and human means to perform teaching (SI-Table 1-B4) and have more limited access to scientific bibliographical databases than research institutions. This condemns France to competence scarcity. To perform the two tasks above, the EU and Member States should learn from this counterexample. They should provide financial and organizational support to retrieve the competence to learn, critically assess and renew phytosociological knowledge.
PREBIC is a multidisciplinary network of scientific experts focused on the prevention of preterm birth through basic, epidemiologic, and applied clinical research. We requested aggregate national-level data on the number of live births and fetal deaths at each completed week of gestation by plurality (singleton or multiple) starting at 22 weeks in 2010. We also asked for separate data on TOP, when these were included in the data sources and could be differentiated from spontaneous stillbirths. When gestational age was missing, we asked countries to include births if birth weight was 500 grams or more. The 22-week GA threshold is recommended by Euro-Peristat for the collection of all data on births in Europe  [20]. If countries could not provide data using these criteria, they were asked to provide available data using their own inclusion criteria, and to specify their inclusion thresholds for live births and stillbirths.
Data came from vital statistics, civil registers and medical birth registers in most countries and from nationally representative surveys of births in Cyprus and in France  [1]. If countries could not provide national data, population-based data from geographically defined regions were accepted. Data for Belgium (BE) came from the regions of Brussels, Wallonia and Flanders; data from the United Kingdom were provided separately by the UK's constituent countries: England and Wales combined, Northern Ireland, and Scotland. Data from Cyprus were from 2007 and data from Canada were from 2008. Data from Canada included all provinces and territories except the province of Ontario. Euro-Peristat also collects information on data quality, management, and data collection procedures  [15]. The sources of data used for each of the countries and their coverage are provided in Supplemental Table  S1.
Outcome Our principal outcome was the singleton very preterm birth rate, defined as all singleton stillbirths and live births before 32 completed weeks of gestation per 1000 total births, excluding TOP if identifiable in the data source. We also computed the singleton live VPT rate (number of singleton live very preterm births per 1000 live births). We limited our comparison to singleton pregnancies, because preterm birth rates are much higher for multiple pregnancies and multiple pregnancy rates differ widely among countries  [9, 21]. In the European countries, Canada and Japan, gestational age was based on the best obstetrical estimate. This estimate can be derived from ultrasound, and other prenatal assessments of gestational length (i. e. last menstrual period, fundal height). In Canada, postnatal assessments may sometimes be used if ultrasound data are missing.
Analysis strategy For this study, we identified countries where differences in registration practices may contribute to variability in rates. First, we assessed whether the data provided by each country met our inclusion criteria: births and deaths starting at 22 weeks of gestation for each completed week of gestation, excluding terminations. We identified countries using different birth weight or gestational age criteria, as well as countries that included TOP in their vital statistics but could not distinguish them from spontaneous births. Next, we calculated the rates of singleton very preterm births for all births less than 32 weeks GA using a lower threshold of 22 weeks GA or national definitions. We then evaluated the influence of periviable births (defined as births at 22-23 weeks) and stillbirths on country rates and rankings by comparing VPT rates with and without these births.
We also calculated percentages of periviable births, and stillbirths (for births ≥22 weeks GA vs. ≥24 weeks GA), among very preterm births, and percent of stillbirths by gestational age subgroups: at 22-23 weeks GA, 24-27 weeks GA, and 28-31 weeks GA. We studied the association between rates for total and live births overall and by gestational age subgroups using Spearman's rank test. Last, we investigated the potential impact of underreporting of stillbirths, after exclusion of births at 22 to 23 weeks, by simulating an extreme situation where a third of stillbirths 24 to 27 weeks of GA were not reported in countries with higher registration thresholds. Data were analyzed using STATA 13. 0 software (StataCorp LP, College Station, TX, U SA).
Strengths and limitations We had access to population-based data by completed week of gestation and plurality compiled using a common protocol  [1]. Countries with varying gestational age or birth weight thresholds for recording stillbirth were identified. We also excluded TOP in countries where they are included in birth registries and identifiable, and flagged countries where TOP could not be removed. However, there were several limitations. We requested data using the best obstetric estimate of gestational age, but did not have further information on how this estimate was derived. While ultrasound dating is the norm, various methods of gestational age assignment are likely used and may impact the preterm birth rate  [25, 26]. We also only had data from one year, which leads to random variation in countries with a small number of annual births.
Funding This study was funded by grants from the  European Commission  for the Euro- Peristat  project:  2010 13 01  and for the Bridge Health project:  664691. The funding agency was not involved in the study. Marie Delnord  received doctoral funding from  Paris Descartes University, Paris ,  France Jennifer L. Richards  received support from the  Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)  of the  National Institutes of Health (NIH)   T32 Predoctoral Training Program in Reproductive, Perinatal , and  Pediatric Epidemiology  under Award Number  T32HD052460   Naho Morisaki  was supported by the  Japan Ministry of Health, Labor and Welfare  ( H28-ICT-001 ) and the  Japan Agency for Medical Research and Development  ( AMED-6013 ). Lucy K Smith is funded by a  National Institute for Health   Research Career Development Fellowship.