dataesr/scientific-paragraphs-categorization huggingface dataset:
Data Sources: We will identify eligible studies by searching the following databases: MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials. Study Selection: We will include all randomized trials and cohort studies published between January 1, 2004, and March 16, 2020. Data Extraction: Data extraction will include information related to study characteristics, population characteristics, clinical criteria, and outcomes. Data Synthesis: We will calculate sensitivity and specificity of each criterion for predicting sepsis and conduct a meta-analysis if the data allow. We will also provide pooled estimates of overall hospital mortality. Conclusions: The potential risk factors, clinical criteria, and illness severity scores from this review which identify patients with infection who are at high risk of developing sepsis-associated organ dysfunction and/or progressing to multiple organ dysfunction or death will be used to inform the next steps of the Pediatric Sepsis Definition Taskforce.
At least 5-10 true positives will be purposely included in the test set. The test set will be created by the principal investigator (K. M. ) and verified by one other Systematic Review Working Group member (L. S. ) before the project is posted to recruit reviewers. Each title will be screened by two reviewers using the predetermined eligibility criteria. Titles eliminated by both reviewers will be rejected and the remaining titles moved to full-text screening. Each remaining full-text article will be screened by two members of the Systematic Review Working Group for inclusion in the final set of articles for data extraction. Conflicts will be resolved by discussion or a third member of the Systematic Review Working Group if consensus is not reached during the discussion. Kappa scores on the level of agreement reached between reviewers at each stage of screening will be reported.
Data Extraction and Management Data from all included full-text articles will be extracted by two Systematic Review Working Group reviewers per citation using a Research Electronic Data Platform (REDCap) platform (32) hosted at the Children's Hospital of Eastern Ontario Clinical Research Unit. Conflicts will be resolved by discussion or by a member of the Systematic Review Working Group if consensus cannot be reached. Data extraction will include information related to study characteristics (i. e. , title, authors, year of publication, country, language, journal, study design, sample size, and inclusion/exclusion criteria); population characteristics (age, sex, admission diagnosis, level of care available, location of the admission within the hospital/clinic, disease classification of population studied, and patient comorbidities); exposure (pathogen, source, community-acquired vs hospital-acquired infection, or sepsis as per Centers for Disease Control and Prevention criteria  [33] , specific definition of sepsis used); clinical criteria (Table  1 ); and outcomes (PICU admission, 28-d mortality, PICU mortality, PICU and/or hospital length of stay, and NPMODS).
Data Synthesis and Analysis We will summarize data on study characteristics, outcomes, and other related variables, criteria/scores reported as well as quality assessment using tables, graphs, and narrative summaries. Continuous outcomes will be summarized using mean and sds or medians with interquartile ranges as appropriate. Binary outcomes will be summarized using frequencies and percentages. We will construct a two-by-two table for each criterion identified in the included studies and will add 0. 5 to all cells if any of the cells are zero. For each criterion, we will calculate its sensitivity and specificity for predicting sepsis, multiple organ failure, or death and report the corresponding 95% CIs. We will also calculate the likelihood ratios for the presence (positive likelihood ratio) or absence (negative likelihood ratio) of each criteria/score and pretest and posttest probabilities of the outcome (sepsis, multiple organ failure, or death).
ACKNOWLEDGMENTS We would like to thank  Kathy Vermoch  and  Lori Harmon  from the  Society of Critical Care Medicine and Katie O'Hearn at the Children's Hospital of Eastern Ontario  for all their help with this project and article. We would also like to thank  Margaret Sampson , librarian at the  Children's Hospital of Eastern Ontario  for her invaluable help in creating and executing the search for this systematic review. We would also like to thank  Ryan Sondarage  and  Supun Kotteduwa Jayawarden  for their remarkable efforts in title/abstract and full-text screening. On behalf of the  Pediatric Sepsis Definition Taskforce :  Luregn J. Schlapbach  ( Co-Chair ),  Paediatric Critical Care Research Group, Child Health Research Centre, The University of Queensland, and Paediatric ICU, Queensland Children's Hospital, Brisbane, QLD, Australia ;  R.
3 ), and (ii) the translation of decisions into socially equitable and ecologically sustainable outcomes (category II, 3b in Fig. 3 ). To do that, we used open coding methods (Ayala-Orozco et al. , 2018), starting with a set of codes that were adjusted as the data were being analysed to ensure maximal homogeneity within subcategories. The dataset collected from the case studies can be found in the supp. material (Section C).
Acknowledgments The authors wish to thank the communities and organisations who shared their experiences through the case studies. We would also like to thank  Lucrecia Estigarribia  for useful comments on the manuscript;  David Gonzalez  and  Sourya Das  for their contribution to the discussions during workshops; and  Brigitte Baptiste  and  Elena Bennett  for their contribution in the early stages of the project. Annesha Chowdhury  provides the photograph about the case study in Darjeeling Himalayas in Fig. 1. Bosco Lliso  proof read the manuscript. This work was supported by the  PEGASuS program of Future Earth  funded by the  Gordon and Betty Moore Foundation  through subgrant  GBMF5433  to the  Basque Centre for Climate Change  ( BC3 ) to support the  EQUIVAL  project and the work of UP, PB and NZ-C.
The authors wish to thank the  Sida funded Swedbio programme at the Stockholm Resilience Centre , the  Programme for Ecosystem Change and Society (PECS) of Future Earth  and the  Future Earth Montreal Global Hub , the  Institute of Ecosystem and Sustainability Research at the Autonomous National University of Mexico , and the  Division of Science Policy and Capacity-Building  ( SC/PCB ) of the  United Nations Educational, Scientific and Cultural Organization (UNESCO) , the  Red Socioecos CONACYT   2017-260483 , CISEN V, The  ValuES  project from  GIZ  supported by the  BMUB  and ecoSERVICES from  Future Earth , and the  Frank Jackson Foundation  for providing support and financial resources. PB enjoyed sabbatical leave during the final iterations of this manuscript and UP enjoyed a research stay at the  University of Life Sciences (Norway)  at the beginning of the research project, funded by the  Basque Government  through an  "Ikermugikortasuna" grant.
With the implementation of the new Activation Control Card (ACT Card)  [6] , evolution calculations are now possible with MCNP 6. 1 and higher versions allowing the creation and transport of delayed particles from non-nuclear materials and fissionable isotopes. The study presented in this paper mainly focuses on the detection of delayed gamma rays emitted by fission fragments of nuclear materials ( 235 U and 239 Pu) or by non-nuclear materials activated during neutron irradiation. The creation of delayed gamma rays from fissionable isotopes is done with the option FISSION=P, and for non-nuclear materials with the option NONFISSION=P. In order not to calculate delayed gamma rays, the options to be used are FISSION=NONE for nuclear materials, and NONFISSION=NONE for non-nuclear materials. The main delayed gamma rays of interest for nuclear materials in this study based on LARA nuclear database  [7]   The 1778 keV delayed gamma ray emitted by 28 Al (T 1/2 = 2.
However, as detailed in  [5] , the uranium and plutonium samples used for this study have important self-shielding factors of respectively 3. 8 and 5. 7, with a large uncertainty due to imprecise knowledge of the geometry of their fissile core. In addition, uncertainties related to delayed gamma ray nuclear data might also be significant. Taking into account these important sources of uncertainties, simulated and experimental net counts are quite consistent, thus validating the use of MCNP 6. 1 Activation Control Card for predicting the order of magnitude of induced-fission delayed gamma ray signal. The experiment vs. simulation comparison is also performed for the net counts of the 1778 keV activation gamma ray due to the aluminum frame bars of REGAIN cell. The experimental net counts measured during a 30 ms gate between the pulses of the neutron generator for a whole 2 h neutron irradiation as presented in Fig.
The decay curves of the 1778 keV activation gamma ray from 28 Al and 1345 keV activation gamma ray from 64 Cu are presented in Fig. 12. The exponential fits of the 1778 keV and 1345 keV decay curves gives 28 Al and 64 Cu half-lifes consistent with theoretical data from LARA nuclear database : T 1/2 sim = 2. 24 ± 0. 006 min vs. T 1/2 th = 2. 2414(12) min for aluminum, and T 1/2 sim = 12. 74 ± 0. 03 h vs. T 1/2 th = 12. 700(2) h for copper.
g. ,  Maley (1970) ,  APLF (1974) ,  Ybert (1979)  and  Bonnefille and Riollet (1980). Pollen nomenclature, which follows the standard defined by the African Pollen Database  (Vincens et al. , 2007) , was based on  Lebrun and Stork (1991-2015). The pollen microflora was composed of 147 taxa. Pollen taxa were grouped according to the phytogeographical and ecological affinity of the parent species following  Lézine et al. (2009)  with dry tropical (including Saharan, Sahelian and Sahelo-Sudanian pollen types), humid tropical (including Sudano-Sahelian, Sudanian, Sudano-Guinean and Guinean pollen types), mangrove, wet indicators, cultivated plants and undifferentiated (including Poaceae) (Table  3 ). Pollen percentages were calculated against a sum excluding mangrove pollen types, wet pollen types and ferns, the percentages of which were calculated separately against a sum including all the pollen grains and fern spores counted (Figure  4 ).
Acknowledgements This work was initiated in the frame of a  CNRS INSU LEFE  research project headed by  M. Carré  and an  IRD scientific network  coordinated by  A. Sifeddine  (" CLIMACTE "). It is an " ACCEDE" Belmont Forum contribution  ( 18 BELM 0001 05 ). Thanks are due to the  Institut de Recherche pour le Développement (IRD) in Senegal  and the  UCAD Geological Department  for logistic support in the field and authorizations and to the  ECLAIRS international laboratory, Dakar  and the  LOCEAN laboratory  for fundings. Thanks are due to  M. Carré ,  R. Cheddadi  and  K. Lemonnier  for field assistance. A. -M. L. is funded by  CNRS  and C. A. K. F. and E. S. by  UCAD. Raw data will be stored at NEOTOMA and are also available on request from the authors.
ABSTRACT Objectives The aim was to provide figures for drug shortages in France and describe their characteristics, causes and trends between 2012 and 2018. Methods Data from the national reporting system from the Agency of Medicine and Health Product Safety (ANSM) was analysed. This database contains information regarding effective and predicted shortages of major therapeutic of interest drugs (ie, drugs whose shortage would be life-threatening or representing a loss of treatment opportunity for patients with a severe disease) which are mandatory reported by marketing authorisation holders to the ANSM. Data are presented as numbers or percentages of pharmaceutical products (ie, the product name and its formulation) reported on shortage between 2012 and 2018. Results There were 3530 pharmaceutical products reported on shortage during the period, including 1833 different active substances.
MeThOdS This observational retrospective study analysed the surveillance reporting system of drug shortages from the ANSM between 2012 and 2018. Since 2012, MAHs are indeed obliged to declare any effective or predicted shortage of MTI drugs to the ANSM. The reporting database contains the information reported by the MAHs via completed declaration forms. The following data were analysed: (1) from declaration forms: dates or report, drugs names, active substances (international non-proprietary names (INN)), routes of administration, setting first impacted by the shortage (community pharmacy and/or hospital), reasons for the shortages (available since 2015); (2) from the marketing authorisation dossier and the summary of the product characteristics: dates and procedures of marketing authorisation grants, storage conditions and (3) ATC codes according to the WHO Collaborating Center for Drug Statistics Methodology.
4 We found that anti-infectives for systemic use represented the first therapeutic class reported on shortage until 2018 (18%) among which antibacterial drugs ranked first each year. This trend is well documented across the USA. Antimicrobials were the most common drug class on shortage in critical care (2001-2016) and emergency medicine practice (2001-2014), representing, respectively, 20% and 24% of US shortages. 19 20 Cephalosporins were the most common antibacterial drug class, in accordance with findings from a US study using the UUDIS database from 2001 to 2013. 26 Shortages of antimicrobials may not have alternative production sources and may thus require the use of less effective or more toxic alternatives,  20 26  leading to worse patient outcomes. 18 In a European survey, antiinfectives were also found to be the most common drugs on shortage in hospital pharmacies in 2013, along with cancer drugs.
Data Extraction and Quality Analysis Two of the authors independently extracted the relevant data from each selected full-text article using a standardized form. In the event of discrepancies between the reviewers, a consensus was reached by discussion. The following information were collected: authors, year of publication, study design, total sample size, sample size for each group, follow-up time, mean age and gender for each group, postoperative procedural and medical complications, pseudarthrosis rate, and mortality. The methodological quality of the randomized studies was assessed using the Cochrane tool. The methodological quality of nonrandomized studies was assessed using the Newcastle-Ottawa Scale. 15  This scale assesses the quality of nonrandomized studies for meta-analyses with a maximum of 9 points.
Statistical Analysis The summary statistics for the effect size of surgical treatment compared with conservative treatment were generated using a random-effect model and a relative risk (RR) with the corresponding 95% confidence intervals (95% CIs). Weighted incidences were also assessed. We explored the publication bias of the studies included in the final analysis using a Begg funnel plot. For each meta-analysis, statistical heterogeneity among studies was explored using the Cochrane Q statistic, study consistency being quantified by means of the I 2 statistic. In the event of significant heterogeneity (P < 0. 10) with no clear explanation for this, a random-effect model was used for data analysis. A P value for the association <0. 05 was considered statistically significant. Combined effect estimates were calculated globally, and according to the study design.
Acknowledgments The authors warmly thank  E. Rossi  and  T. Esposti Ongaro , and the editor,  S. Parman , for their constructive comments which greatly improved the original version of this manuscript. We thank  H. Bouquerel ,  A. Limare ,  T. Rivet , and  A. Souilah  for technical support and  A. Pennacchioni  and  A. Sarelli  for helping with preliminary experiments. This work was partially funded by the  RAVEX  Project ( ANR  contract  ANR-16-CE03-0002 ), the  STRAP  Project ( ANR  contract  ANR-14-CE03-0004 ) and is part of  A. Michaud-Dubuy 's PhD thesis. This study contributes to the  IdEx  project " Université de Paris " ( ANR-18-IDEX-0001 ).
ACKNOWLEDGMENTS We thank  S. D. Bartlett  for fruitful discussions. We thank  RIKEN CEMS Emergent Science Research Support and Microwave Research Group at Caltech  for technical assistance. Part of this work was financially supported by  CREST ,  JST  ( JPMJCR15N2 ,  JPMJCR1675 ), the  ImPACT Program of Council for Science, Technology and Innovation (Cabinet Office, Government of Japan ),  JSPS KAKENHI  Grants No. 26220710 , No. 18H01819 , No. 19K14640  and No. 16K05411 , RIKEN Incentive Research Projects, The  Murata Science Foundation   Research Grant , and  MEXT   Quantum Leap Flagship Program  ( MEXT Q-LEAP)  Grant Number  JPMXS0118069228. T. O. acknowledges support from  JSPS KAKENHI  Grants No. 16H00817  and No. 17H05187 ,  PRESTO  ( JPMJPR16N3 ),  JST ,  Yazaki Memorial Foundation for Science and Technology   Research Grant, Advanced Technology Institute Research Grant ,  Izumi Science and Technology Foundation   Research Grant ,  TEPCO Memorial Foundation   Research Grant , The  Thermal & Electric Energy Technology Foundation   Research Grant , The  Telecommunications Advancement Foundation   Research Grant ,  Futaba Electronics Memorial Foundation   Research Grant , and  MST   Foundation Research Grant.
Nevertheless, there is still a great need to provide more data for the Energies 2020, 13, 1135 2 of 12 development of methods for designing geopolymers. The geopolymerization process is strongly dependent on the source, composition, and particle size of the aluminosilicates; thus, a database on the chemistry, reactivity, and dissolution mechanisms of various precursors must be completed  [5]. There are many examples of geopolymer mixes and alkali-activated materials (AAM) in the literature. The properties of those binders depend on the chemical composition of the source material (precursor)  [7]. High-and low-calcium alumicosilicates have been considered. Aluminosilicate systems based on FA with low calcium content require a heat treatment curing cycle, which makes these materials well suited for prefabrication and precast manufacturing processes  [8] [9] [10] [11] , but they jeopardize their sustainable character because they require a significant amount of thermal energy to set and harden.
Magnetic cloud sample In situ measurements of the magnetic field and plasma properties in the interplanetary medium have been carried out by several spacecraft since the 1960s. In particular, the Wind spacecraft has been observing the interplanetary medium since 1994 at 1 au. For this study we used data from two instruments, the Magnetic Field Instrument (MFI) and the Solar Wind Experiment (SWE), with a temporal cadence of 60 s for (MFI) and 92 s for (SWE), which we downloaded from https://cdaweb. sci. gsfc. nasa. gov/pub/ data/wind/mfi/mfi_h0 and https://cdaweb. sci. gsfc. nasa. gov/pub/data/wind/swe/swe_h1/ , respectively. We examined the data for a set of MCs observed by Wind between 1995-2012 that were analysed by  Lepping et al. (1990 Lepping et al. ( , 2011)). The list of MCs can be found at https://wind.
Next, we fitted the SEA results with the Lundquist and Gold-Hoyle models. Both models closely represent the profiles of the SEA; the largest deviation is obtained for the field intensity B(t) with SEA profiles flatter than those of both models. Still, the Lundquist model best fits the SEA results of the B components while it is almost a perfect fit for the SEA profiles of the normalised field components (unit vectors). This allows a precise determination of the twist profile because it is derived from the normalised components. Furthermore, the resulting impact parameter, p, obtained from the fitting procedure, is within the interval [0. 13, 0. 2] and with a mean of 0. 17. These results are consistent with the mean value of the impact parameter of the MCs data set. Next, we computed the twist profile, τ, from three different methods.
Acknowledgements. S. D. and V. L. acknowledge partial support from the  Argentinian grants UBACyT (UBA)  and  PIP-CONICET-11220130100439CO. This work was partially supported by a one-month invitation of P. D. to the  Instituto de Astronomía y Física del Espacio  and by a one-month invitation of S. D. to the  Observatoire de Paris. P. D. thank the  Programme National Soleil Terre  of the  CNRS/INSU  for financial support. S. D. is member of the  Carrera del Investigador Científico, CONICET. V. L. is fellow of CONICET.
CASE DESCRIPTION AND RESULTS Before child's treatment procedure, we get a consent form signed by the mother and/or father (legal guardian) regarding the treatment plan, participation in the training process and the use of anonymous patient data related to the medical history. Permission form is approved by Ministry of Health. A 9-year-old boy visited healthcare professionals in October 2015. The patient felt nausea, vomiting and headache episodes, which had been lasting for approximately 2 years. These complaints were investigated and no pathology was found. After 1 month, neck-muscle rigidity manifested for the first time and the patient referred to the hospital. During the appointment, a blood test was taken for suspected borreliosis and tick-borne encephalitis. As a result, borreliosis was diagnosed and etiological treatment was prescribed amoxicillin 500 mg (Sandoz GmbH; Kundl, Austria) taken 3 times daily.
, 2007). Thus, banks may prefer multiple-bank lending when the bank has lower equity, when the cost of monitoring is high, or when the profitability of the firm is low. Bonfim et al. (2018)  use a unique dataset that covers all bank loans granted in Portugal and find that when a small firm borrows from one additional bank, the interest rate on its bank loans decreases. This is mainly due to the fact that multiple bank relationships reduce asymmetric information related to the financial contract for small firms. Deeper insights are provided by Catherine Refait-Alexandre and Stéphanie Serve in their article "Multiple banking relationships: Do SMEs mistrust their banks?" published in this special issue. The authors put into perspective both financial and management approaches in explaining the probability of SMEs engaging in single or multiple banking relationships.
Data extraction and synthesis The following data were extracted from the selected publications: PubMed ID (PMID), first author, publication year, type of population, mean age of study participants and standard deviation if provided, number of study participants, female gender, outcome relating to a common frailty score/instrument, outcome(s) relating to partial aspects of frailty, short description of the intervention and its duration, positive outcome(s) relating to frailty or aspects of frailty. Methodological quality, or risk of bias of clinical trials, was calculated by using a three-item questionnaire, known as the Jadad score  [19]. Drop-outs/withdrawals, randomization, blinding, and the quality of latter two items are assessed and a score derived ranging from 0 (very poor) to 5 (rigorous)  [19].
| Molecular testing Concerning HHV-6 status, both donor and recipient pretransplant blood samples were retrospectively tested. At baseline, both kidney recipient serology and PCR were negative for HHV-6. HHV-6 PCR of recipient's nails were negative, confirming the absence of ici-HHV-6 at baseline. Conversely, HHV-6A was identified in a donor blood sample with a viral load of 7. 40 log 10 copies/10 6 cells. Such a level of viral load in an immunocompetent subject suggested a case of iciHHV-6. In order to analyze the relationship between the strain from the donor and the recipient, sequencing of U38, U39, U69, and part of U100 viral genes was performed for both strains. U38, U39, and U100 sequences in all samples (from donor blood, colon biopsy, and blood samples from the recipient), were identical to the German iciHHV-6A HP73F12 strain (GeneBank accession number KY315540).