dataesr/scientific-paragraphs-categorization huggingface dataset:
Standard errors in parentheses. Panel-robust standard errors. Notes: Choice-based sampling is realized on observation-level. Sampled firm-year observations were completed with available observations for the same panel from the original database. WEML weights were calculated for each year separately, but this table presents only the average WEML weights over our analysis period. Choice-based sampling is realized on the full sample of manufacturing industry. The sub-samples of the food industry and of the manufacturing industry (excluding food industry) were extracted from the manufacturing industry choice-based sample IV instrumental variable, WEML weighted exogenous maximum likelihood weight *p < 0. 05, **p < 0. 01, ***p < 0. 001 Table13Parameter estimates and probit regression of firm bankruptcy using WEML on choice-based samples, manufacturing industry, 2001-2012 mean(X i,t -1 , X i,t -2 , X i,t -3 ).
Acknowledgments We are extremely grateful to  Patrick Sevestre  for his very helpful discussions and suggestions. We would also like to thank  Elisabeth Kremp  for her guidance and comments on an earlier version of this paper. The first author wishes to dedicate this paper to the memory of  Jean-Pierre Huiban , her PhD co-supervisor, who unfortunately passed away during the course of preparing this paper. This research was improved by the comments from the participants at the internal seminar of  Banque de France Companies' Directorate , the lunch seminar at Sciences Po, the  INRA   ALISS internal seminar , the  Insolvency workshop at Université Paris Nanterre , ADRES conference in Paris, the  SAEe conference in Palma de Mallorca , and the AAEA & WAEA Joint Annual Meeting in San Francisco.
Standard errors in parentheses. Panel-robust standard errors. Notes: Choice-based sampling is realized on observation-level. Sampled firm-year observations were completed with available observations for the same panel from the original database. WEML weights were calculated for each year separately, but this table presents only the average WEML weights over our analysis period. Choice-based sampling is realized on the full sample of manufacturing industry. The sub-samples of the food industry and of the manufacturing industry (excluding food industry) were extracted from manufacturing industry choice-based sample. Comparison of parameter estimates between (1) and (2) Table 10 (continued) mean(X i,t -1 , X i,t -2 , X i,t -3 ) Food industry (1) Manufacturing industries Manufacturing industries (excluding food industries) (2) (all sectors) (3) Annual dummies Yes Yes Yes Number of obs.
Farm Data and Characteristics Sixteen dairy farms from the two cantons were assessed; Thurgau represented the lowland and Grisons the mountain region. In each region, four farms were collaborating in contract rearing (hereafter "collaborating farms"), and four farms were not participating in contract rearing (hereafter "non-collaborating farms"). Collaborating and non-collaborating dairy farms were randomly selected from those that offer apprenticeship positions. Since authorization to do so requires additional training for the farmer, we assumed that the farms in the sample were more advanced farms, i. e. , farms that apply good management practices and are well-informed about new technical developments. Data on farm characteristics and agricultural practices were collected during farm visits or provided directly by the farmers.
Data collection was based on two datasets developed within the EU FP7 project CANTOGETHER. One set contained data needed for LCA  (Teuscher et al. , 2014) , and the other contained supplementary agronomic and economic data  (Regan et al. , 2016). Table  1  gives an overview over some farm characteristics. Farms in the sample were larger and had more animals than the average dairy farm in Switzerland, which had (in 2012) 24 ha UAA and 23 dairy cows. Except for one mountain farm, milk yield per cow also lay above the Swiss average of 6000 kg of milk  (TSM, 2013). On lowland farms, most forage was home-grown, mainly grass, and whole-crop maize (silage or dried pellets). Most concentrate was purchased; only a small percentage was home-grown. In addition to producing feed, five lowland farms also grew cash crops.
Life Cycle Inventory The farmers provided the main data used to calculate the LCI, which included data about yields, animal numbers, purchased inputs such as feed or energy carriers, housing infrastructure and manure management, machinery, and detailed information about field-management practices such as date, type, quantity applied, and application method for each fertilization or cropprotection event. The LCI itself was then calculated with a tool developed for the CANTOGETHER project (CANCalc,  Teuscher et al. , 2014). In the present study, the LCI consisted of an inventory of farm inputs, linked to upstream processes from ecoinvent v2. 2 (ecoinvent Centre, 2010) and the Swiss (3) The SPACSYS (soil-plant-atmosphere continuum system) model, version 5. 1  (Wu et al. , 2015) , to predict N leaching and runoff, and nitrous oxide (N 2 O) emissions.
For deforestation, virtual conversion of the two conventional non-collaborating farms into organic farms reduced impact to the point that non-collaborating farms no longer differed from collaborating farms. This was due to only one feed ingredient: soybean meal. Soybean meal from Brazil is considered to be the main source for deforestation in conventional concentrate. The organic concentrate used in this study from the SALCA database  (Nemecek et al. , 2010)  contained no soybean meal from deforested areas. In contrast, the conventional concentrate included soybean meal from the global market and thus also from Brazil. Consequently, use of organic concentrate led to much lower deforestation. However, this result is valid only as long as indirect land-use change is excluded from the assessment  (Meyfroidt et al.
agricultural LCA (SALCA,Nemecek et al. , 2010)  database, and farm outputs including direct emissions. The following tools and models were used to calculate direct emissions:(1) A dataset of organic and mineral fertilizers, with their nutrient contents and availability to plants, based on data from Flisch et al. (2009), Nemecek and Kägi (2007)  and fertilizer producers. (2) A tool developed by project partner SP Technical Research Institute of Sweden (formerly SIK) to predict emissions from enteric fermentation, manure management and application (Berglund and Cederberg, 2014).
ACKNOWLEDGMENTS We wish to express our gratitude to the farmers who provided the data for our assessment. We also thank Rémy Teuscher, Peter Koch, Hisko Baas, and Jens Lansche for the development of the CANTOGETHER LCA tools, and Lianhai Wu for his support with SPACSYS. We would also like to thank Daniel U. Baumgartner for his support and proofreading of the manuscript, and Thomas Nemecek for his methodological advice during the project. This work was funded under the EU Seventh Framework Program by the CANTOGETHER project (no. 289328): Crops and ANimals TOGETHER. The views expressed in this work are the sole responsibility of the authors and do not necessarily reflect the views of the European Commission.
In this article, we first present HATSim according to the Overview, Design concepts, and Details (ODD) protocol that is classically used to describe agent-based models, then, in a second part, we present predictive results concerning the evolution of Human African Trypanosomiasis in the village of Lambi (Cameroon), in order to illustrate the interest of such a tool. Our results are consistent with what was observed in the field by the Cameroonian National Control Program (CNCP). Our simulations also revealed that regular screening can be sufficient, although vector control applied to all areas with human activities could be significantly more efficient. Our results indicate that the current model can already help decision-makers in planning the elimination of the disease in foci.
b. gambiense disease variants in northwest Uganda and southern Sudan  [1]. The model we present herein is based on the methodology used by Müller et al. [23] , and its development was based on the main HAT focus in Cameroon in the 2000s, the Bipindi focus. This model is different from Müller's work by its incorporation of a spatial map corresponding to the occupation of space within this area. HATSim was developed using the Cormas Ò system  [2]  that relies on an agent-based model and that was written in the Smalltalk language, using VisualWorks software Ò. This is a powerful simulation tool for improving how we understand the complex interactions between natural and social dynamics. The Overview, Design concepts, and Details (ODD) protocol that was proposed by  Grimm et al. in 2006 [13]  allowed us to use a standardized method to describe HATSim.
At the stage of data analysis, sensitivity analyses consisting of various statistical models that make different assumptions about the data should be carried out. The EMA Guideline on clinical trials in small populations also states that the use of Bayesian methods  [15]  could be advantageous when faced with small datasets because these methods offer a way to combine knowledge from previous data or prior knowledge with data from a study, although introducing prior beliefs is often a concern in drug regulation. As with sensitivity analyses, a variety of reasonable prior distributions should be combined with data from studies to ensure that conclusions are not too much based on a specific prior distribution  [12]. The U. S. Food and Drug Administration (FDA) published a draft guidance on rare diseases in August 2015  [16].
Our review may offer a way for progressing the study of rare diseases in general. The remainder of this paper is organized as follows. In Section 2, we describe the literature searches undertaken to identify suitable primary studies for the two illnesses of interest (Section 2. 1) and the process of extracting relevant data from those studies (Section 2. 2). Section 3 summarizes the main findings; in Section 3. 1 and Section 3. 2 study selection and study characteristics, respectively, are discussed and in Section 3. 3 the methodological quality of the studies is appraised. In Section 4, the review's "take-home" messages are summarized and the strengths and weaknesses of the evidence are discussed. In Section 5, a general interpretation of the results in the context of other evidence is provided and suggestions for future research are made.
Systematic literature search and article selection To choose appropriate literature search strategies for the two illnesses under investigation, the PICOS framework  [21]   Observational studies are deemed to be relevant if at least 20 people were contained in the treatment arm. This imposed restriction eliminates individual case reports and small case series and also may reduce publication bias. Based on these PICOS specifications, publications were identified from the electronic databases PubMed and Cochrane Central Register of Controlled Trials (CEN-TRAL), by using the following search strategies: All titles and abtracts were screened independently by two reviewers (SU, CR). Full papers were reviewed if at least one reviewer considered a paper relevant for the review. Finally, the reference lists of all qualifying articles were examined to supplement the search.
Data extraction, risk of bias assessment tool and quality scales Using an electronic spreadsheet, the following data items were extracted by one reviewer and verified by another: reference, aims/objectives of the study, study design, endpoints of interest, description of patient characteristics at the beginning of study, method of randomization, method of blinding, type of intervention and intervention group, specification of the control group, withdrawals, dropouts, patients lost to follow-up, and statistical methodologies used to analyse the patient collectives. It is important to assess risk of bias in studies as differences in risk of bias can help explain variation in the results of studies included in a systematic review. The Cochrane Collaboration's recommended tool for assessing risk of bias in RCTs is a domain-based evaluation, in which critical assessments are made separately for different domains and then judgements are assigned to relate the risk of bias to each of the domains  [22, 23].
Study selection Figures 1 and 2 represent the PRISMA four-phase flow diagrams for the different phases of identification and selection of primary studies on evaluating interventions in paediatric MS and CJD, respectively. Using the search strategies mentioned above, 130 abstracts (124 abstracts) on paediatric MS (CJD) were retrieved from the PubMed and CENTRAL databases. The database searches were conducted on December 15th, 2015. On the basis of an initial screening of the titles and abstracts, 108 (114) records were excluded on paediatric MS and CJD, respectively. It should be mentioned that for paediatric MS, full-text versions of two records that have been written in Russian and which may have been eligible for inclusion in the review were not available  [26, 27]. Scanning the reference lists of the remaining papers revealed a further two (six) papers that may have been eligible for inclusion in the review.
Unfortunately, the single RCT available on patients with paediatric MS suffers from several weaknesses including a very small sample size and lack of blinding. Blinding to subcutaneous interferon-beta-1a treatment could be obtained by allocating matching placebo intramuscular injections to the control group (see for example ClinicalTrials. gov identifier: NCT00441103 for a completed RCT in adult patients with MS). One promising finding from the RCTs in patients with CJD is that multicentre, occasionally multinational studies, fast enrolment and rigorous study methods with a sufficient number of participants and low risk of bias can be achieved for treatment of a rare, rapidly progressive neurological disorder. The present review has some limitations. Firstly, our literature searches were focused on retrieving evidence on two specific rare diseases.
Secondly, the imposed restriction of considering only studies with at least 20 participants receiving the intervention of interest implies that some evidence for evaluating therapies in paediatric MS and CJD is excluded from this review. On the basis of an initial screening of the titles and abstracts found via the databases PubMed and CENTRAL for paediatric MS (CJD), 18  (13)  records out of a total of 130 (124) records, most of which are single case reports, are excluded because they did not meet our imposed restriction. Finally, we only assessed the risk of bias for RCTs. For controlled studies the domains in the standard tool of the Cochrane Collaboration could also usefully be assessed when the allocation is not randomized  [23]. As suggested in  [23] , for non-randomized studies an additional domain to assess the risk of bias due to confounding should be added.
Furthermore, ethical challenges of paediatric studies do exist  [48]. For example, a placebo-controlled design requires that some participants forego active or possibly effective therapy, which could be a more serious issue in children compared to adults. As a remedy, one might consider alternative designs instead such as add-on studies, active comparator arm studies, dose-ranging studies or deferred-treatment arm studies. A phase III, doubleblind, randomised, active-controlled trial to evaluate safety and efficacy of fingolimod versus interferon beta-1a is currently recruiting paediatric patients with MS (ClinicalTrials. gov identifier: NCT01892722). In this RCT, double-dummy masking is required for blinding. Placebo intramuscular injections are obtained by allocating syringes matched in appearance to the active interferon beta-1a intramuscular syringes.
Generalized evidence synthesis then essentially comes down to making decisions on how and to what extent to discount the observational data. In  [55] , patients were randomly assigned (in a 4:1 ratio) to either treatment or placebo. For the evaluation of the placebo effect, data from eight previous trials in patients with ankylosing spondylitis were included. The information contained in these trials was transformed into an informative prior distribution by means of the methodology described in  [59]. The ongoing trial in paediatric Alport patients aims to combine the treatment effect estimates from the randomized comparison with Alport registry data  [56]. A meta-analysis combining evidence on the effects of doxycycline in patients with early CJD from both a randomized study and a non-randomized study is the subject of current research of members of the team of co-authors of this review  [57].
Funding This research has received funding from the  EU 's  7th Framework Programme  for research, technological development and demonstration under grant agreement number  FP HEALTH 2013 -602144  with project title (acronym) " Innovative methodology for small populations research " (InSPiRe). The funder had no involvement in the study design; in the collection, analysis and interpretation of the data; in the writing of the report; and in the decision to submit this article for publication.
A 10-camera system positioned around the court during matches tracked the ball's trajectory and players' movements throughout points (Hawk-Eye Innovations Ltd. , Basingstoke, England). Ball flight information was in the form of trajectory data (x, y, z coordinates as a function of time) while player movement data were in the form of x, y coordinates. The data from selected points were input into the LTA rendering engine (Julien Pansiot, London, UK, 2013) through which animated videos of the data were generated for use with VLC media player (VideoLAN, Paris, France). The principle difference between the two display conditions was that postural information of the players was not visible in the animated condition. In place of seeing the players and their rackets, participants saw a blue and a red cylinder representing each player and the ball as a yellow dot, while rackets were not visible.
In both display conditions trials were occluded at the opponent's racket-ball contact using Pinnacle Studio 15 editing software (Pinnacle, Ottawa, Canada). <<Insert Figure  1  here>> Experimental trials were made up of footage from 90 rallies, with the final occluded shot played by the opponent to one of four areas on the court. Those shots the opponent hit on which the first bounce landed before or after the service line were classified as short and deep respectively, while those shots which landed to the right or left of the centre line were classified as such. The number of shots played to the four areas of the court on the final occluded shot was: deep-left (32); deep-right (32); short-left (13); and short-right (13). The order of the bounce location of the opponent's final occluded shot was randomized across trials and conditions.
Data Analysis Judgment accuracy was reported as the percentage of correct anticipation judgments relative to the actual final ball bounce location of the occluded shots. To determine whether participants could anticipate more effectively than chance, paired samples t-tests were carried out to compare depth, direction, and combined judgment accuracy of the two groups with judgment accuracy that would be expected due to chance. To examine the extent to which skilled and less-skilled participants can use contextual information alone and both contextual and postural information to inform their judgments, a 2 × 2 (Display [normal video, animated] × Group [skilled, less-skilled]) multi-factorial MANOVA with repeated measures was conducted for judgment accuracy, with the percentage of correct depth, direction, and combined judgments serving as the dependent variables.
Williams and Davids (1997) originally collected verbal reports of thoughts in conjunction with eye-movement data to verify the information participants were attending to in a soccer anticipation task, finding that the relationship between visual fixation and the information participants verbally reported they were attending to, was dependent on the nature of the task. In a task which evoked the use of foveal vision for information extraction, the area of the display fixated on was also verbally reported by participants, whereas when information was extracted through the use of peripheral vision, participants reported attending to different information to that which they were fixating on during the task. Skilled performers have been shown to exhibit different gaze behaviors to less-skilled performers (e.
Materials, Apparatus, and Set-Up The experimental set-up and visual angle employed was the same as in Experiment 1. In addition, participants' gaze was recorded using a Mobile Eye eye-tracking system (Applied Science Laboratories, Bedford, MA, USA) during trials. The head-mounted system is integrated in a pair of glasses connected to a digital transmission unit, which is wirelessly connected to the recording device and worn by the participant in a small backpack. The gaze recording system records two images with two separate cameras; an image of the participant's eye and the scene image. The system integrates these two images to create one video recording of the scene video with a superimposed gaze cursor. The gaze data were analyzed using ASL Results Plus (Applied Science Laboratories, Bedford, MA, USA).
Gaze data Search rate data were made up of the mean number of fixations, mean number of fixation locations, and mean fixation duration. A fixation was defined as the participant's point of gaze staying stationary for three frames or more (>/= 100 ms) within 1. 5° of movement tolerance (see  Williams & Davids, 1998). To determine any between-group differences, independent t-tests were conducted for search rate, with mean number of fixations, mean number of fixation locations, and mean fixation duration as the dependent variables and Group as the independent variable. Percentage viewing time was defined as the portion of time the participant spent fixating on a particular area of interest. Areas of interest were: the (receiving) player; the opponent; the ball flight; the near side of the court; the far side of the court; and the play area (any other area of the display within which the ball could potentially travel throughout the trial); and unclassified areas.
The last time series    was constructed by Maria Arias at the Federal Reserve Bank of St. Louis using the raw data from the HAVER database listed in Table 11. The nominal interest rate faced by US nonfinancial business (annual frequency) is computed as    =    to obtain the interest rate with quarterly frequency. We then calculate the real interest rate    by deflating    with the US GDP deflator (series GDPDEF from FRED) and rescaling it to be quarterly gross interest rate. All estimations are performed with the Dynare software (see http://www. dynare. org/) using 6 MCMC chains, each with 60,000 draws and acceptance rate between 0. 25 and 0. 33. The observed time series are linked to the log-linearized model through the following measurement equations: Supplementary material related to this article can be found online at https://doi.
(2013) (see their appendix for data descriptions). The last time series    was constructed by Maria Arias at the Federal Reserve Bank of St. Louis using the raw data from the HAVER database listed in Table 11. The nominal interest rate faced by US nonfinancial business (annual frequency) is computed as    =    to obtain the interest rate with quarterly frequency. We then calculate the real interest rate    by deflating    with the US GDP deflator (series GDPDEF from FRED) and rescaling it to be quarterly gross interest rate. All estimations are performed with the Dynare software (see http://www. dynare. org/) using 6 MCMC chains, each with 60,000 draws and acceptance rate between 0. 25 and 0. 33. The observed time series are linked to the log-linearized model through the following measurement equations: Supplementary material related to this article can be found online at https://doi.